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distribution p(A) is typically incorporated in a Bayesian framework (e.g. enforcing that neighboring pixels are highly correlated). An additional difficulty here is that A is a structured geometric object: an
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accessible measure of location. One option is to use skew versions of know distributions that leave the mode or median of the distribution at the origin. The main objective of this project is to explore, from
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complex, multi-objective optimization problem. It involves searching over materials, geometries and fabrication parameters to balance competing objectives such as coherence time, anharmonicity and
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, Bayesian inference, and decoding/encoding methods. (Optional) Conduct in vivo calcium imaging experiments in C. elegans to study how neural circuits generate behavior. Engage in creative, hypothesis-driven
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, custom-trained neural networks, and related tools. Analyze and interpret high-dimensional neural datasets using systems neuroscience approaches such as neural networks, Bayesian inference, and decoding
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· Demonstrable problem-solving skills · Ability to propose and apply novel (literature based) and innovative ideas for solving a problem Desirable · Knowledge of Bayesian uncertainty techniques
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Research Engineer/Postdoctoral Position Decision and Bayesian Computation (DBC) – Epiméthée (EPI) Laboratory Institut Pasteur, Paris | 25 rue du Docteur Roux, 75015 Paris Position Overview We
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Areas (Codes 25–29) 1. Machine Learning (Code 25) Objectives: Support UFABC’s undergraduate and graduate programs, strengthen research in Machine Learning, and expand English-taught course offerings
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. Training will cover modelling, quantitative analysis, and laboratory methods. OBJECTIVES O1. Build a spatiotemporal lineage atlas of the pre-implantation human embryo. The student will assemble high-content
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multidisciplinary teams, supporting colleagues to ensure successful delivery of shared objectives. E6 Experience of making distinct contributions to identifying and pursuing research funding (or equivalent business