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Field
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Experience using Linux or Unix, and high-performance computing systems Experience with Python, R, or another scientific programming languages Experience with AI/ML approaches Familiarity with tools like BLAST
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experience developing deep learning models using frameworks using PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as GDAL
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desirable. Experience with fluid–structure interaction (FSI) modelling is an additional advantage. Experience with scientific programming (e.g., Python, MATLAB, C++ , or similar languages) is advantageous
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analyzing genomic, transcriptomic, proteomic, spatial multi-omics, imaging, or other high-dimensional biological datasets. · Proficiency in R and/or Python for computational biology and bioinformatics
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, imaging, or other high-dimensional biological datasets. · Proficiency in R and/or Python for computational biology and bioinformatics analyses. · Excellent analytical, organizational, written, and verbal
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programming skills in Python and/or R; experience with STATA, MATLAB, or SQL is advantageous. Experience with aviation, airport, airspace, flight trajectory, or transportation datasets. Strong publication
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estimation. Experience with convex or semidefinite optimisation, variational methods, or computational complexity. Proficiency in relevant scientific programming or quantum-software tools, such as Python
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listed in the project description above (ideally SAR for cryosphere applications) Strong programming skills (preferably Python or MATLAB) Strong background in statistics Fulfillment of the requirements
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using python, MATLAB, etc. Ability to support organisation of webinars and remote and in person training activities Publications in Q1 journals on the above topics Please see the attached job description
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, and modeling tools (e.g., Python, MATLAB, TCAD, photonic simulation software). Strong analytical, problem-solving, communication, and teamwork skills, with the ability to work independently in a