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, working with the Medical Image Analysis and AI research group within the School of Computing Science. The successful candidate will develop novel computational frameworks integrating biophysical tumour
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into experimental animals. Assist with and eventually independently perform surgery and perfusions on experimental animals. Collect tissue and fluid samples (e.g., body fat, brain tissue, blood) from experimental
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image acquisition. 4. To participate in the out-of-hours first opinion service if required, ensuring adequate cover is available for the provision of direct supervision, advice and expertise when required
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engagement•Interest in translating scientific insights into policy and practice Selection process How to Apply Please submit: A motivation letter explaining your interest in this PhD and how your
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, tasks, duties, and assignments. Furthermore, job duties, responsibilities and activities may change at any time with or without notice. Required Qualifications Education: PhD in Biology related field
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patients with cardiogenic shock and cardiothoracic surgery. You will work at the frontline where engineering, physiology, and critical care converge to shape the future of life-saving therapy. PhD Position
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.8b07216 [8] Dahlia Saad, PhD from Ecole Centrale de Lyon, “What happens at the nanometric scale at the liquid/solid interface? Implementation of an Atomic Force Microscope for 3D-AFM imaging of liquid/solid
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and coordinate elements of the postgraduate MSc in Medical Imaging and Radiation Therapy online. The successful candidates will have a BSc or MSc in Radiation Therapy, or other related disciplines and
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, pharmacology, cell and molecular biology, imaging and nuclear medicine, ophthalmology, rehabilitation, tissue engineering, food animal, equine, and small animal medicine and surgery, and others. Research
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 15 days ago
AI-assisted research processes across computational biology. Prototype, benchmark, and iteratively improve agentic systems with a strong focus on robustness, transparency, and reproducibility. Conduct