Stavroula Mougiakakou
6 months ago
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PhD Position in Mechanism-Informed Multimodal AI University of Bern in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
Switzerland
University
University of Bern
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About this position
The ARTORG Center for Biomedical Engineering Research at the University of Bern is a leading transdisciplinary center dedicated to advancing medical technology research. The Artificial Intelligence in Health and Nutrition (AIHN) laboratory within ARTORG is offering a fully funded PhD position focused on mechanism-informed multimodal AI models. This opportunity is ideal for candidates interested in developing next-generation AI methods that integrate mechanistic knowledge with data-driven approaches, contributing to a large international research consortium.
The successful candidate will engage in interdisciplinary research, collaborating with engineers, computer scientists, healthcare professionals, and industrial partners. Key research topics include the development of mechanism-informed multimodal AI models, mechanism formalisation and discovery using knowledge-driven, data-driven, and hybrid approaches, and causal inference and modelling (including structural, temporal, and dynamic causal models). The project aims to address unmet clinical needs and envision future challenges in diagnosis, monitoring, and treatment, ultimately creating innovative healthcare technology solutions.
Applicants should possess an MSc in computer science, engineering, applied mathematics, or a related field. Essential qualifications include experience with causal inference methods (such as SCMs and Bayesian networks), knowledge of dynamical systems or systems biology, experience with multimodal biomedical data, familiarity with knowledge graphs and ontologies, and proficiency with generative AI models (including VAEs, diffusion models, and multimodal transformers). A strong background in machine learning, mathematical modelling, probability, and optimization, as well as experience in Python and deep learning frameworks (e.g., PyTorch), is required. Excellent command of English and a commitment to multidisciplinary research are also expected.
The position is funded for up to four years, with salary provided according to Swiss University regulations. The University of Bern offers an international environment, excellent research opportunities, and promotes healthy work-life balance and safe working conditions. It is an equal opportunity employer and strives to increase the number of women at all levels in its faculties.
To apply, candidates should send their application to Prof. Stavroula Mougiakakou ([email protected]). Applications must include a motivation letter, detailed curriculum vitae, abstract of the master thesis, and contact details of two referees, all combined into a single PDF file. The expected start date is July 2026, and applications will be reviewed until the position is filled.
For further information about the AIHN laboratory and the ARTORG Center, visit the lab website. The position is part of a larger international consortium, offering close collaboration and exposure to cutting-edge research in biomedical engineering and AI.
Funding details
Available
What's required
Applicants must hold an MSc in computer science, engineering, applied mathematics or a related field. Required skills include experience with causal inference methods (such as SCMs and Bayesian networks), knowledge of dynamical systems or systems biology, experience with multimodal biomedical data, familiarity with knowledge graphs and ontologies, and experience with generative AI models (such as VAEs, diffusion models, and multimodal transformers). A strong background in machine learning, solid understanding of mathematical modelling, probability, and optimization, proficiency in Python and deep learning frameworks (e.g., PyTorch), and excellent command of English are essential. Commitment to multidisciplinary research is expected.
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Professors
Professor at University of Bern
Switzerland
Research Interests
Clinical Nutrition
Dietetics
Nutrition
Cardiometabolic Health
Diet
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.