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Field
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need to be able to analyse data and interpret findings from your research, including large and complex datasets combining different modalities (in particular behavioral and neuro-cognitive methods, but
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architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch, including training and evaluating models on GPU/HPC infrastructure; • experience working with
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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scientific applications. The CGR lab conducts research at the cutting edge of computational biology and bioinformatics. We aim to understand human genome variation and evolution across different genomic
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, particularly in light of the rise in chronic diseases, the necessary strengthening of prevention efforts, or the possible resurgence of epidemics; socio-economic inequalities and differing capacities to access
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, and Den Otter, Weindel, Stuit, Van Maanen, Plos Computational Biology, 2026 for more information about these methods. The goal of the project is to be able to track differences in strategy use between
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; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
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outputs. Proficiency in scientific programming and computational tools commonly used in numerical modeling and environmental data analysis, such as Python, MATLAB, Fortran, C/C++, or comparable languages
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make a difference in the world! Position Information Texas A&M AgriLife Research at Temple is seeking a highly motivated scientist with expertise in crop modeling, remote sensing, and geospatial