PhD Candidate - Time-Series ML & Anomaly Detection

Halmstad University; Halmstads kommun; On-site; SEK 301,000 - 402,000; Full time

Job summary

Halmstad University invites applications for a PhD student position in the School of Information Technology. The project focuses on robust anomaly detection in time-series using diffusion methods and foundation-models, with applications in ENGADE/UNIFY-AI collaborations.

The role includes coursework, research, and potential teaching duties. Applicants should hold an MSc in a related field, have strong ML/AI knowledge, and excellent programming skills.

Qualifications

• M.Sc. degree in computer science, computer engineering, electrical engineering, Physics, or closely related field with focus on ML/AI.
• Strong English communication skills.
• Solid knowledge of ML, AI, data mining, or signal processing.
• Excellent programming abilities and analytical problem-solving.

Responsibilities

• Conduct research on diffusion-based anomaly detection within time-series foundation-model framework.
• Publish findings in peer-reviewed venues and contribute to doctoral coursework.
• Carry out teaching and supervision duties up to 20%.
• Collaborate with international teams on ENGADE and UNIFY-AI projects.

Skills

Machine learning

Artificial intelligence

Data mining

Signal processing

Education

M.Sc. degree in computer science / computer engineering / electrical engineering / physics or related field

Job description

Halmstad University invites applications for a PhD student position in the School of Information Technology. The project focuses on robust anomaly detection in time-series using diffusion methods and foundation-models, with applications in ENGADE/UNIFY-AI collaborations.

The role includes coursework, research, and potential teaching duties. Applicants should hold an MSc in a related field, have strong ML/AI knowledge, and excellent programming skills.