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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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a focus on synaptic plasticity, NMDA receptor signaling, 2-photon optogenetics, and advanced 2-photon imaging. We are particularly interested in candidates with strong expertise in whole-cell patch
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) modeling, computational oncology/biology, kinetic modeling, advanced image processing. The candidate should be highly motivated with a strong interest and commitment to research. Curiosity and creativity
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. Prior experience in at least one of the following is a requirement: physiologically based pharmacokinetic (PBPK) modeling, computational oncology/biology, kinetic modeling, advanced image processing
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: physiologically based pharmacokinetic (PBPK) modeling, computational oncology/biology, kinetic modeling, advanced image processing. The candidate should be highly motivated with a strong interest and commitment
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clinical research, leveraging cutting-edge approaches in molecular biology, bioinformatics, biomarkers, and regenerative medicine. We are looking for a highly motivated postdoctoral fellow to join our
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. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health, bio-signal processing, and wearable
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PyTorch, TensorFlow, and Scikit-learn. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health