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Field
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, Rutgers Biomedical and Health Sciences (RBHS) takes an integrated approach to educating students, providing clinical care, and conducting research, all with the goal of improving human health. Aligned with
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Engineering, Biomedical Engineering, Mechanical Engineering or a related field. Nano/microfabrication experience Prior experience with designing and testing in vitro or implantable sensors Prior experience with
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degree (PhD, MD, or equivalent) or Master’s degree in a relevant field (e.g., Computer Science, Biomedical Engineering, Public Health, Surgery) Experience in clinical research, data analysis, or machine
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The Royal Veterinary College, University of London | Potters Bar, England | United Kingdom | about 18 hours ago
central London. The successful applicant will work on PRECISE-AI (Probabilistic Reasoning with Circuits for Safe and Explainable Artificial Intelligence), a research project funded by the Engineering and
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one-million-euro Commercialization Fund. FAST-Pore brings together an interdisciplinary team to develop solid-state nanopore technologies for biomedical diagnostics and some innovative engineering
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Electrical Engineering, Biomedical Engineering, Computer Science, Neuroscience, Robotics, AI Ethics or a related field. Preferred Qualifications: • Strong publication record and clear research trajectory
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project researchers You will report to the Head of Department. Your competences You have academic qualifications at PhD level, for example within the following areas: Medical imaging, biomedical engineering
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: Job Requirements: Required: PhD in computer science, biomedical informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based
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scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex
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central London. The successful applicant will work on PRECISE-AI (Probabilistic Reasoning with Circuits for Safe and Explainable Artificial Intelligence), a research project funded by the Engineering and