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machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal behavior and neuronal activities in circuits of murine models of 22q11.2 and
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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of the art data science approaches (text mining, machine learning, AI) to comprehensively highlight yet undiscovered virus/host/environment relationships and annotate potentially putative new spillover
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expertise in robotics, sensing, machine learning, biomechanics, and haptics. The project is funded by a NWO VIDI grant to the PI and provides financial security, access to state-of-the-art equipment, travel
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PhD in Data Science, Computational Social Science, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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”. Are you excited about the opportunities that data science in nutrition—especially the role of targeted metabolic modelling, machine learning and AI offer in developing effective personalized nutrition
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Excellent organizational, communication, and teamwork skills Experience with dynamic causal modelling (DCM), machine learning or related computational approaches are an asset Roles and Responsibilities
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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grant when extending an offer. The successful candidate will hold a PhD, MD, DDS, or equivalent advanced degree, with a strong track record of academic excellence demonstrated by high-quality publications