PhD in computerized image processing and physics-informed machine learning for green hydrogen production Uppsala University in Sweden

Uppsala University is advertising a PhD position in computerized image processing and physics-informed machine learning for green hydrogen production at the Department of Information Technology in Sweden. The project sits at the intersection of computer science, machine learning, computer vision, 3D image processing, physics-informed machine learning, materials science, and chemical engineering, with a focus on improving proton exchange membrane water electrolyzers (PEMWE) for green hydrogen production.

The research will develop automated pipelines for segmenting and analysing X-ray computed tomography (XCT) images of thermally sprayed titanium layers, extract physically meaningful microstructural descriptors, build probabilistic surrogate models and digital twins, and use Bayesian experimental design and Bayesian optimization to guide process optimization. The work is supervised by Ida-Maria Sintorn (Professor in digital image processing) and Jens Sjölund (Assistant Professor in AI), in collaboration with Alleima and Sandvik.

Eligibility highlights include a relevant Master’s degree or equivalent credits in engineering physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, or applied mathematics. Strong programming skills in Python, excellent academic results, good English communication, and a creative, structured problem-solving style are requested. Experience in image analysis, deep learning, optimization, numerical linear algebra, statistical machine learning, visualization, and software engineering is considered an advantage.

The position is a temporary full-time PhD employment (100%), with doctoral studies as the main duty and up to 20% departmental duties such as teaching and administration. The application deadline is 7 May 2026, and the expected start date is 1 September 2026 or as agreed. Applicants must submit a cover letter, CV, degree documents, thesis or draft, relevant publications, and reference contacts through Uppsala University’s recruitment system.