Om tjänsten
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 This is a full-time position available from November 1st 2026 (or as soon as possible) for a period of four years to a
doctoral degree (extended with one year after one year, subject to satisfactory progress of the PhD study). Since the employment
also includes teaching responsibilities corresponding to a maximum of 20% of full-time, the position is extended with the same
amount of time as the teaching activities . 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