Phd opportunity in medical physics, neuro-oncology, therapeutic ultrasound, and ai for life sciences

Ph D opportunity in Medical Physics, Neuro AI, Biomedical AI, and AI for Life Sciences University of Rome Tor Vergata — Medical Physics Section, Department of Biomedicine and Prevention DEADLINE APPROACHING - JUNE 4th!!! We are welcoming expressions of interest from motivated prospective Ph D candidates who would like to join our research group at the interface of medical physics, artificial intelligence, computational neuroimaging, molecular AI, physiological systems modelling, therapeutic ultrasound, and translational biomedical research. Our lab develops quantitative, computational, and physics-informed methods to study complex biological and clinical systems. Current research spans Neuro AI, brain decoding, MRI/PET/f MRI/diffusion MRI/EEG/MEG analysis, biomedical image and signal processing, AI for life sciences and medicine, multimodal data integration, molecular and systems-level modelling, radiomics and precision oncology, AI-assisted radiotherapy, brain–body and autonomic modelling, focused ultrasound and Thera FUS technologies, ultrasound-mediated therapeutic delivery, neuromodulation, nanomedicine, and safe-by-design modelling. |The successful candidate will join an active and highly interdisciplinary environment with numerous projects funded by European programmes, NIH, national agencies, and regional funding bodies. They will have ample exposure to our network of collaborators across Europe, the United States, and other international research centres, with opportunities to contribute to ambitious projects connecting AI, physics, imaging, neuroscience, molecular data, physiology, and clinical translation. We welcome candidates from backgrounds including physics, medical physics, biomedical engineering, computer science, data science, applied mathematics, bioengineering, neuroscience, biology, biotechnology, medicine, computational biology , or related areas. The ideal candidate is curious, rigorous, collaborative, and motivated to work across disciplinary boundaries. Experience with programming, machine learning, image or signal analysis, neuroimaging, molecular data, physiological modelling, statistics, or biomedical datasets is welcome, but different profiles will be considered. Lab website: Interested candidates should send a single PDF including a short cover letter, CV, academic background, and any relevant research or technical experience to: [email protected] Please use the subject line: "Ph D Expression of Interest "