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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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the basis for an animal welfare indicator, review and build on existing welfare frameworks, and translate these into a practical metric that can be applied within HESTIA. You will use Python to develop models
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, including imaging mass cytometry (IMC) Advanced programming and data analysis skills in R and/or Python Downloading a copy of our Job Description Full details of the role and the skills, knowledge and
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and experience in one or more open-source languages (e.g. Python, R). Prior experience/knowledge of computational psychiatry methods for modelling cognitive tasks. Experience in the use of neuroimaging
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statistical/computational analysis (e.g. R, Python, ELAN); Strong written and oral communication skills; Ability to work independently and collaboratively across disciplines. We regret to inform that only
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related field. Strong background in statistical modelling, high-dimensional data analysis, and machine learning. Proficiency in R; Python or related computational experience is advantageous. Good analytical
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are no longer practical. This project aims to automate anomaly detection (identifying missing, stuck, and suspicious data) at high temporal resolution (five-minute intervals) by combining Python-based rule-based
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analysis. Excellent programming skills in Python and experience with deep-learning frameworks (preferably PyTorch). Experience developing, training, validating, and optimising machine-learning models
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modeling. Proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow. Experience handling large geospatial, atmospheric, or remote sensing datasets is preferred. Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
, Competencies, and Experience Strong programming skills in Python and/or R. Experience analyzing high-dimensional biological data, especially single-cell sequencing data. Strong statistical and quantitative