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Field
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learning and statistics. A good command of Python programming is essential, as is a good command of English, both spoken and written. Skills in optimal transport theory and knowledge of generative models
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are experimentally driven and supported by COMMLab, 6GSPACE Lab, HybridNetLab, QCILab, TelecomAI Lab, CSAT Lab, our SW Simulators, and our Facilities. For further information, you may refer to https://www.uni.lu/snt
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analysis is expected; familiarity with scientific programming environments (e.g. Python, R, or similar) is highly desirable interest in policy-relevant science and sustainability frameworks strong motivation
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related field experience with numerical models and/or large observational datasets strong skills in scientific programming (e.g. Python, Fortran, or similar) ability to work independently and in
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analysis is expected; familiarity with scientific programming environments (e.g. Python, R, or similar) is highly desirable Interest in policy-relevant science and sustainability frameworks Strong motivation
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(http://www.hogberglab.net/ ). You will contribute to the Dura-store project that is a part of the European Innovation Council’s Pathfinder Challenge for DNA-based digital data storage, aiming to use bio
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Python programming is desirable. The candidate will be based in the laboratory space in the School of Pharmacy, UCC, working with Professor Abina Crean and Dr. Sonja Vucen. Within our group we strive
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(Python required; R, C++ appreciated). Strong interest in network modeling, multi-criteria optimization, or graph theory. Skills in statistics and data analysis. Experience in 3D modeling, phenotyping
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for advanced data analysis and/or experimental control (e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in
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related field experience with numerical models and/or large observational datasets strong skills in scientific programming (e.g. Python, Fortran, or similar) ability to work independently and in