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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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requirements A PhD in a relevant subject such as mathematics, computer science, physics, engineering, or a related discipline. Candidates who have not yet defended their PhD are eligible to apply, provided
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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and Fluidigm technologies at UTHSC. Qualifications PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, or a related field. Strong background in machine learning, data
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electrophysiological and calcium imaging recording techniques to assess glia and neural activities. Perform pharmacological modulation to investigate neural circuit activity in the context of metabolism and energy
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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problem solving strategies used in nature and to ground these ideas by fostering deep collaborations with experimental biologists. Most recently, we have been interested in neural circuit computation and
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Learning (DL) tools tailored specifically to the particularities of TCR interactions. As part of the Deep Immune Receptor Modeling (DIRM) grant from the NNF Data Science Collaborative Research Programme
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a multidisciplinary and integrated approach combining genomics, computational and structural biology, neuroscience, and data and decision sciences. The Human Technopole Foundation is looking for one
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medical degree programme. Academic staff contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over