Open positions
We are always happy to hear from motivated people interested in AI for medicine. Pick the path that fits you best.
There are no open calls at the moment. New positions are announced in our news.
No open call that fits? Send us a spontaneous application for PhD, research assistant or postdoc roles. Please include:
Email subject: [BEAR] Spontaneous application – Name Surname
Bachelor’s and Master’s students at the University of Trento can do their thesis with us on AI for medicine, from methods to clinical applications. Write to us with your study programme and the topics you like.
We welcome visiting PhD students and researchers, and collaborations with clinical partners, hospitals and companies working on medical data.
Students
MSc thesis topics from the BEAR group. Every thesis develops a novel module, architecture or learning strategy for an open problem in medical imaging, and validates it in a clinically relevant domain: radiology, neuro-radiology, neuro-oncology or ophthalmology. Have your own idea? Propose it to us.
Combine complementary imaging modalities and clinical data to make models more robust, interpretable and transferable, even when some data are missing.
Reconstruct missing or corrupted imaging modalities from the available ones, so that patients with incomplete acquisitions are not discarded.
Generate anatomically plausible medical images that are consistent with given disease and treatment conditions.
Forecast how a disease will evolve from longitudinal scans, predicting both the future spatial disease state and the corresponding image.
Generate structured radiology reports from medical images, linking every statement to the image region that supports it.
Build a pipeline that recognises artefacts, corrupted inputs and low-confidence cases, and adapts preprocessing, inference or human review accordingly.
One framework for detection, segmentation and classification together with prognosis, supporting interpretable clinical decisions.