Lediga jobb som Doktorand hos Högskolan i Halmstad

• Doctoral student (Licentiate) in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  The information-driven care research program has a continued need to strengthen doctoral-level research on AI and ML in healthcare, encompassing main research projects such as CAISR Health, a KK Foundation-funded research profile on responsible and trustworthy AI/ML in healthcare, and Informationsdriven nära vård, which analyses the full patient care chain and trajectory to identify how AI, ML and information-driven approaches can provide more insights to improve care. The program needs a doctoral student to conduct research towards a licentiate degree within this area, contributing new methods and insights within the triple-helix collaboration between academia, regions, municipalities, and industry partners. Tasks include:

  - Conduct doctoral-level research towards a licentiate degree within the information-driven care research program, focusing on one or more of the following research areas: Representation learning, Vertical federated learning, Time-series analysis and modelling, Uncertainty quantification, Multimodal / heterogeneous data fusion, Sequential and trajectory modelling, Graph-based learning, Explainable and interpretable AI, Causal inference, Privacy-preserving machine learning

  - Analyse patient trajectories across the full care chain, working with multi-source clinical and care data from regions, municipalities, and industry partners

  - Deliver activities in relation to the broader research project portfolio (e.g. CAISR Health and Informationsdriven nära vård), including analysis, data preparation, and reporting

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the licentiate programme

  - Participate actively in the information-driven care research program's activities and in collaboration with regions, municipalities, and industry partners within the triple-helix model

  - Teaching and supervision duties (up to 20%) can be included

  This is a position to a licentiate degree. Subject to securing additional funding, there may be a possibility to extend the position and continue towards a full PhD after the licentiate degree.

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English and Swedish are required.

  - Strong knowledge of machine learning is required, with experience in one or more of representation learning, (vertical) federated learning, time-series modelling, uncertainty quantification, or deep learning, including transformer-based and more recent architectures like Mamba.

  - Experience in one or more related areas such as multimodal data fusion, sequential and trajectory modelling, graph-based learning, explainable AI, causal inference, or privacy-preserving machine learning is required.

  - Programming skills in Python are required.

  - Experience in healthcare applications and interdisciplinary research is required, as is prior research experience (e.g. thesis work or publications). 

  - Relevant publications in high-tier venues within AI and ML are required.

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

• Doctoral student in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  Halmstad University has received funding for the ENGADE and UNIFY-AI projects. Both projects address the development of robust machine-learning methods for time-series data, but from complementary perspectives. ENGADE focuses on developing theoretical foundations and new diffusion-based methods for anomaly detection in time series. Its research includes multivariate and multiscale time-series modelling, concept drift, and explainability. UNIFY-AI focuses on developing a time-series foundation model trained on heterogeneous fleet data and adapting it to industrial aftermarket and uptime applications. Its use cases include anomalous brake-wear detection, together with brake-pad wear prediction and energy-storage-system degradation forecasting. UNIFY-AI also studies robustness to missing signals, new operating conditions, and distribution shifts over time. The scientific overlap between the projects concerns robust anomaly detection in heterogeneous and evolving time-series data. A PhD student is needed to investigate how diffusion-based anomaly-detection methods can be combined with representations learned by time-series foundation models. The research will examine whether reusable representations learned from heterogeneous data can support anomaly detection across different operating conditions while remaining robust to missing signals and changes in the data distribution. The PhD student will undertake a coherent research project within this shared area. The student will contribute to the diffusion-based anomaly-detection objectives of ENGADE and to the foundation-model-based anomaly-detection and robustness objectives of UNIFY-AI. This requires hiring a PhD student with a focused research profile in machine learning for time series. Tasks include:

  - Research on diffusion-based anomaly detection within the time-series foundation-model framework developed in UNIFY-AI. The work will contribute to ENGADE through the development of theoretically grounded diffusion-based methods for anomaly detection and to UNIFY-AI by supporting its anomaly-detection applications on heterogeneous vehicle data.

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the doctoral programme

  - Teaching and supervision duties (up to 20%) can be included

   

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English is required.

  - Strong knowledge of machine learning, artificial intelligence, data mining, or signal processing is required.

  - Excellent programming skills are required.

  - Analytical problem solving and organizational abilities are required. 

   

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Information for International Applicants

  Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:

  International staff support

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

• Doctoral student (Licentiate) in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  The information-driven care research program has a continued need to strengthen doctoral-level research on AI and ML in healthcare, encompassing main research projects such as CAISR Health, a KK Foundation-funded research profile on responsible and trustworthy AI/ML in healthcare, and Informationsdriven nära vård, which analyses the full patient care chain and trajectory to identify how AI, ML and information-driven approaches can provide more insights to improve care. The program needs a doctoral student to conduct research towards a licentiate degree within this area, contributing new methods and insights within the triple-helix collaboration between academia, regions, municipalities, and industry partners. Tasks include:

  - Conduct doctoral-level research towards a licentiate degree within the information-driven care research program, focusing on one or more of the following research areas: Representation learning, Vertical federated learning, Time-series analysis and modelling, Uncertainty quantification, Multimodal / heterogeneous data fusion, Sequential and trajectory modelling, Graph-based learning, Explainable and interpretable AI, Causal inference, Privacy-preserving machine learning

  - Analyse patient trajectories across the full care chain, working with multi-source clinical and care data from regions, municipalities, and industry partners

  - Deliver activities in relation to the broader research project portfolio (e.g. CAISR Health and Informationsdriven nära vård), including analysis, data preparation, and reporting

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the licentiate programme

  - Participate actively in the information-driven care research program's activities and in collaboration with regions, municipalities, and industry partners within the triple-helix model

  - Teaching and supervision duties (up to 20%) can be included

  This is a position to a licentiate degree. Subject to securing additional funding, there may be a possibility to extend the position and continue towards a full PhD after the licentiate degree.

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English and Swedish are required.

  - Strong knowledge of machine learning is required, with experience in one or more of representation learning, (vertical) federated learning, time-series modelling, uncertainty quantification, or deep learning, including transformer-based and more recent architectures like Mamba.

  - Experience in one or more related areas such as multimodal data fusion, sequential and trajectory modelling, graph-based learning, explainable AI, causal inference, or privacy-preserving machine learning is required.

  - Programming skills in Python are required.

  - Experience in healthcare applications and interdisciplinary research is required, as is prior research experience (e.g. thesis work or publications). 

  - Relevant publications in high-tier venues within AI and ML are required.

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

• Doctoral student in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  Halmstad University has received funding for the ENGADE and UNIFY-AI projects. Both projects address the development of robust machine-learning methods for time-series data, but from complementary perspectives. ENGADE focuses on developing theoretical foundations and new diffusion-based methods for anomaly detection in time series. Its research includes multivariate and multiscale time-series modelling, concept drift, and explainability. UNIFY-AI focuses on developing a time-series foundation model trained on heterogeneous fleet data and adapting it to industrial aftermarket and uptime applications. Its use cases include anomalous brake-wear detection, together with brake-pad wear prediction and energy-storage-system degradation forecasting. UNIFY-AI also studies robustness to missing signals, new operating conditions, and distribution shifts over time. The scientific overlap between the projects concerns robust anomaly detection in heterogeneous and evolving time-series data. A PhD student is needed to investigate how diffusion-based anomaly-detection methods can be combined with representations learned by time-series foundation models. The research will examine whether reusable representations learned from heterogeneous data can support anomaly detection across different operating conditions while remaining robust to missing signals and changes in the data distribution. The PhD student will undertake a coherent research project within this shared area. The student will contribute to the diffusion-based anomaly-detection objectives of ENGADE and to the foundation-model-based anomaly-detection and robustness objectives of UNIFY-AI. This requires hiring a PhD student with a focused research profile in machine learning for time series. Tasks include:

  - Research on diffusion-based anomaly detection within the time-series foundation-model framework developed in UNIFY-AI. The work will contribute to ENGADE through the development of theoretically grounded diffusion-based methods for anomaly detection and to UNIFY-AI by supporting its anomaly-detection applications on heterogeneous vehicle data.

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the doctoral programme

  - Teaching and supervision duties (up to 20%) can be included

   

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English is required.

  - Strong knowledge of machine learning, artificial intelligence, data mining, or signal processing is required.

  - Excellent programming skills are required.

  - Analytical problem solving and organizational abilities are required. 

   

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Information for International Applicants

  Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:

  International staff support

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

• Doctoral student in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  Halmstad University has received funding for the ENGADE and UNIFY-AI projects. Both projects address the development of robust machine-learning methods for time-series data, but from complementary perspectives. ENGADE focuses on developing theoretical foundations and new diffusion-based methods for anomaly detection in time series. Its research includes multivariate and multiscale time-series modelling, concept drift, and explainability. UNIFY-AI focuses on developing a time-series foundation model trained on heterogeneous fleet data and adapting it to industrial aftermarket and uptime applications. Its use cases include anomalous brake-wear detection, together with brake-pad wear prediction and energy-storage-system degradation forecasting. UNIFY-AI also studies robustness to missing signals, new operating conditions, and distribution shifts over time. The scientific overlap between the projects concerns robust anomaly detection in heterogeneous and evolving time-series data. A PhD student is needed to investigate how diffusion-based anomaly-detection methods can be combined with representations learned by time-series foundation models. The research will examine whether reusable representations learned from heterogeneous data can support anomaly detection across different operating conditions while remaining robust to missing signals and changes in the data distribution. The PhD student will undertake a coherent research project within this shared area. The student will contribute to the diffusion-based anomaly-detection objectives of ENGADE and to the foundation-model-based anomaly-detection and robustness objectives of UNIFY-AI. This requires hiring a PhD student with a focused research profile in machine learning for time series. Tasks include:

  - Research on diffusion-based anomaly detection within the time-series foundation-model framework developed in UNIFY-AI. The work will contribute to ENGADE through the development of theoretically grounded diffusion-based methods for anomaly detection and to UNIFY-AI by supporting its anomaly-detection applications on heterogeneous vehicle data.

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the doctoral programme

  - Teaching and supervision duties (up to 20%) can be included

   

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English is required.

  - Strong knowledge of machine learning, artificial intelligence, data mining, or signal processing is required.

  - Excellent programming skills are required.

  - Analytical problem solving and organizational abilities are required. 

   

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Information for International Applicants

  Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:

  International staff support

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

• Doctoral student in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  Halmstad University has received funding for the ENGADE and UNIFY-AI projects. Both projects address the development of robust machine-learning methods for time-series data, but from complementary perspectives. ENGADE focuses on developing theoretical foundations and new diffusion-based methods for anomaly detection in time series. Its research includes multivariate and multiscale time-series modelling, concept drift, and explainability. UNIFY-AI focuses on developing a time-series foundation model trained on heterogeneous fleet data and adapting it to industrial aftermarket and uptime applications. Its use cases include anomalous brake-wear detection, together with brake-pad wear prediction and energy-storage-system degradation forecasting. UNIFY-AI also studies robustness to missing signals, new operating conditions, and distribution shifts over time. The scientific overlap between the projects concerns robust anomaly detection in heterogeneous and evolving time-series data. A PhD student is needed to investigate how diffusion-based anomaly-detection methods can be combined with representations learned by time-series foundation models. The research will examine whether reusable representations learned from heterogeneous data can support anomaly detection across different operating conditions while remaining robust to missing signals and changes in the data distribution. The PhD student will undertake a coherent research project within this shared area. The student will contribute to the diffusion-based anomaly-detection objectives of ENGADE and to the foundation-model-based anomaly-detection and robustness objectives of UNIFY-AI. This requires hiring a PhD student with a focused research profile in machine learning for time series. Tasks include:

  - Research on diffusion-based anomaly detection within the time-series foundation-model framework developed in UNIFY-AI. The work will contribute to ENGADE through the development of theoretically grounded diffusion-based methods for anomaly detection and to UNIFY-AI by supporting its anomaly-detection applications on heterogeneous vehicle data.

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the doctoral programme

  - Teaching and supervision duties (up to 20%) can be included

   

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English is required.

  - Strong knowledge of machine learning, artificial intelligence, data mining, or signal processing is required.

  - Excellent programming skills are required.

  - Analytical problem solving and organizational abilities are required. 

   

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Information for International Applicants

  Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:

  International staff support

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

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  Visa mer

• Doctoral student in machine learning

  Arbetsgivare / Ort:Högskolan i Halmstad / Halmstad

  Omfattning / Varaktighet:Vanlig anställning / 6 månader eller längre

  Lönetyp: Fast månads- vecko- eller timlön

  Ansök senast 19 oktober (9 dagar kvar)

  Publicerad: 2026-10-06

  Källa: Arbetsförmedlingen

  Ansök här

  Om jobbet

  Halmstad University

  Work at a University where different perspectives meet!

  Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University's education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University's two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.

  More information about working at Halmstad University

  The School of Information Technology

  Halmstad University’s School of Information Technology (ITE) is a renowned multi-disciplinary institution with around 155 employees from 20 different countries. ITE is internationally recognised for its applied research and collaborative initiatives, focusing on smart technology and its practical applications. 

  Within ITE, our students and researchers engage in diverse areas of study, including electronics, AI, information-driven healthcare, autonomous vehicles, social robotics, and digital design. We offer a comprehensive range of educational programmes, ranging from undergraduate to doctoral levels, as well as professional development opportunities. 

  Research is conducted within the University’s research programmes, especially Information Driven Care (IDC), Re-Imagining Future Smart Living – beyond the Living Lab (REBEL), Learning in a Digitalised Society (LeaDS) and the Future Industry Research Programme (FIRP). 

  ITE is home to Leap for Life, an innovation centre for information-driven care, as well as the Electronics Centre in Halmstad (ECH), a collaborative space for electronic development. 

  More information about the School of Information Technology

  Description

  Halmstad University has received funding for the ENGADE and UNIFY-AI projects. Both projects address the development of robust machine-learning methods for time-series data, but from complementary perspectives. ENGADE focuses on developing theoretical foundations and new diffusion-based methods for anomaly detection in time series. Its research includes multivariate and multiscale time-series modelling, concept drift, and explainability. UNIFY-AI focuses on developing a time-series foundation model trained on heterogeneous fleet data and adapting it to industrial aftermarket and uptime applications. Its use cases include anomalous brake-wear detection, together with brake-pad wear prediction and energy-storage-system degradation forecasting. UNIFY-AI also studies robustness to missing signals, new operating conditions, and distribution shifts over time. The scientific overlap between the projects concerns robust anomaly detection in heterogeneous and evolving time-series data. A PhD student is needed to investigate how diffusion-based anomaly-detection methods can be combined with representations learned by time-series foundation models. The research will examine whether reusable representations learned from heterogeneous data can support anomaly detection across different operating conditions while remaining robust to missing signals and changes in the data distribution. The PhD student will undertake a coherent research project within this shared area. The student will contribute to the diffusion-based anomaly-detection objectives of ENGADE and to the foundation-model-based anomaly-detection and robustness objectives of UNIFY-AI. This requires hiring a PhD student with a focused research profile in machine learning for time series. Tasks include:

  - Research on diffusion-based anomaly detection within the time-series foundation-model framework developed in UNIFY-AI. The work will contribute to ENGADE through the development of theoretically grounded diffusion-based methods for anomaly detection and to UNIFY-AI by supporting its anomaly-detection applications on heterogeneous vehicle data.

  - Publish research findings in peer-reviewed scientific venues

  - Complete relevant doctoral coursework as part of the doctoral programme

  - Teaching and supervision duties (up to 20%) can be included

   

  Qualifications

  Only those who are or have been admitted to third-cycle courses and study programs at a higher education may be appointed to doctoral studentships. (The Higher Education Ordinance Chapter 5 Section 3). The student’s ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5 Section 5). 

  - A M.Sc. degree (or equivalent, corresponding to at least 240 ECTS credits including a degree project) in computer science, computer engineering, electrical engineering, Physics, or a closely related field with focus on machine learning and AI.

  - Good communication skills in English is required.

  - Strong knowledge of machine learning, artificial intelligence, data mining, or signal processing is required.

  - Excellent programming skills are required.

  - Analytical problem solving and organizational abilities are required. 

   

  Salary

  Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

  Application

  Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page). 

  How to design your application 

  General Information

  We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.

  Read more about Halmstad University

  Information for International Applicants

  Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:

  International staff support

  Arbetslivserfarenhet

  • Doktorand (meriterande)

  Arbetsgivare

  Högskolan i Halmstad
  Kristian IV:s väg 3
  30118 Halmstad

  Webbplats: http://www.hh.se/omhogskolan/jobbahososs.2064.html
  

  Ansökan

  Ansök senast 19 oktober (9 dagar kvar)

  Ansök här

  Visa mer

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