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Applications of Physics to Medicine or a closely related field. A strong background in programming (e.g., Python, or similar languages) is essential, as the project involves computational analysis and data
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analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g., GraphPad Prism, R, or Python
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy
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Engineering or Computer Science. We would also like to see experience in: Machine Learning, Optimisation, Python, finite elements How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and
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connectivity and brain function. You have affinity with working with large datasets and have knowledge of data analysis and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with
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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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geophysics, physics, applied mathematics, or computer science will be considered. Expertise in high-level programming language like MATLAB or Python is essential. Where to apply Website https://emploi.cnrs.fr
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background in applied mathematics, computational mathematics, computer science, physics, or engineering is suitable. Basic programming experience (e.g., C, C++, Julia, MATLAB, Python, or similar) is necessary
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equipment (e.g., 3D scanning, surface inspection). Familiarity with data analysis tools (e.g., MATLAB, Python, or similar) and basic knowledge of machine learning is an advantage. Familiarity with research