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) at the Faculty of Health, Medicine and Life Sciences. TGX is an interdisciplinary research environment where computational scientists, molecular biologists, clinicians, and nutrition researchers collaborate
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collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python and relevant machine learning frameworks such as PyTorch
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mechanisms underlying risk and resilience. You will work with a rich multimodal dataset and collaborate within an international network spanning computational psychiatry, clinical psychology, and neuroscience
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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workflows. You have an interest in, or experience with, machine learning approaches for scientific data analysis. You have a strong interest in interdisciplinary research and enjoy collaborating with
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imaging datasets Ensure robust experimental design and reproducible research practices Publish in leading international journals and conferences Collaborate with interdisciplinary academic and clinical
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for collaboration with experimental groups working on physical learning in electronics, mechanics, and living flow networks (Physarum Polycephalum). For more information about our work, see: [1] Stern, Hexner, Rocks
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industrial partners. Our group offers an open and collaborative environment in which we focus on hands-on learning and personal growth of all group members. We are looking for excited and talented candidates
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at the intersection of reinforcement learning and stochastic optimization developing novel methodologies that advance both theoretical insights and practical applications collaborating across disciplines and contribute
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as part of the FlexLab AI Innovation Lab, a collaboration between Radboud University, Alliander, Stedin, the Netherlands Organisation for Applied Scientific Research (TNO), Eindhoven University