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advanced analytical skills including statistical programming in Python, Stata, R, and/or SAS • Excellent communication and presentation skills • An ability to work both independently and in teams Benefits
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the research activities entrusted to the officer take place: This ANR project lies at the interface between statistical learning (mainly deep learning) and combinatorial optimization (mainly stochastic and
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results, and discussions of possible new approaches with team members and the Principal Investigator. Qualifications Required Qualifications: PhD in Statistics, Biostatistics, Computer Science, Electrical
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
epidemiologic methods, causal inference, and statistics. Proficiency required in statistical software (e.g., R, SAS, Python). Preferred Qualifications, Competencies, and Experience - Special Physical/Mental
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Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Application Deadline 28 Feb 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0
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Posting Details Position Information Fiscal Year 2025-2026 Position Title Postdoctoral Associate, Management Science and Systems Classification Title Postdoctoral Associate Department Management Science and Systems Posting Number P260054 Posting...
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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datasets (e.g., RNA-Seq, epigenetics, cancer genomics, or metabolomics). Statistical Knowledge: Strong understanding of algorithmic, statistical, and ontological concepts in biology. Communication: Excellent
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, applied/computational algebraic geometry, data science/networks or a related discipline, and possess sufficient specialist knowledge in applied topology and/or algebra, random topology, algebraic statistics
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engineering pipelines. Implement models in Python using frameworks such as PyTorch, TensorFlow. Perform statistical analyses and model benchmarking against existing methods. Collaborate with wet-lab scientists