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Field
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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
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.) Data analysis and statistics (R, Python) Qualified applicants should send their CV, a statement of research interests and the contact information of two referees before March 9 to david.bikard@pasteur.fr
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cancer biology, molecular/cellular biology, genomics, or immunology with expertise in gene editing technology and NGS; flow cytometry and cell sorting; and bioinformatic and data integration, R/Python
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, Labview, Python and/or C++. Requirements: PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal
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relevant areas. Has strong ML/AI programming skills (Python: PyTorch, numpy, pandas) and R. Fluent in using UNIX. Publications in related journals is a plus. Baylor College of Medicine is an Equal
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geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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is a plus. Candidates should also demonstrate strong skills in Python (for ML/NLP tasks) and R (for statistical modeling or data analysis), as both will be actively used in the research workflow
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with
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date). Strong background in power systems analysis (OPF, state estimation) and numerical optimization/control. Proficiency with Python/MATLAB and power-system toolchains (e.g., MATPOWER/OpenDSS