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interpreting large datasets using statistical programming languages (e.g. R, Python etc.) Proven independent working style, technical problem solving, data analysis and generation of novel ideas Proficient
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2 Apr 2026 Job Information Organisation/Company École Normale Supérieure Department Physics Research Field Physics » Statistical physics Researcher Profile First Stage Researcher (R1) Positions
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: UNMC is an Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 25 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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of LHC data, based on solid C++ and Python expertise, is strongly appreciated. Ability to work in a large international collaboration is a must. Fluency in English, speaking and writing (B2 minimum) is
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description. The applicant must have excellent professional proficiency in English (written and spoken). Required: Strong knowledge of how to use AI and large language models (LLMs) for data extraction
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. You will have demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single
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regularly publish at top ACM conferences and HCI journals, in interdisciplinary venues such as the Big Data & Society journal as well as across venues in the humanities and social sciences. Terms