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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
the theoretical foundations of data science and AI. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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-series data, or other high-dimensional biomedical datasets. Strong foundation in signal processing, statistical analysis, computational modeling, or algorithm development. Ability to process, clean
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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the UAB Division of Endocrinology, Diabetes and Metabolism. Integrated Physiology and Translational Clinical Research in Diabetes and Metabolic Diseases. The Basu Program, founded over 25 years ago at Mayo
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Department of Mathematics
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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; Experience with EO remote sensing algorithm development and EO product validation; Experience with open source and computing programming using Python and C/C++. Experience in the following areas will be
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and porting of scalable science applications and algorithms for OLCF and other leadership computers. Debugging and tuning applications for high performance. Developing performance models of existing
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quantum matter and quantum computation. Our research includes (1) AI for Quantum: developing advanced AI algorithms grounded in physical principles and machine learning theory to tackle key challenges in