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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
, Artificial Intelligence, Neural Networks, Computational Biology, Bioinformatics, Biomedical Informatics or a related field. Programming experience in a language such as Python or R. Experience in writing grant
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, molecular biotechnology and computational sciences. The modern Campus harbors the buildings of the science faculties and institutes, in direct vicinity to the University Hospital Heidelberg, the Max Planck
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year of a PhD program who are looking to postpone the formal economics job market and build a strong academic record. The position does not require teaching, but it may be possible to get teaching
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by the Netherlands Organisation for Scientific Research (NWO) programme GroenvermogenNL. In Europe, the Netherlands ranks as the second-largest hydrogen producer. As it stands, the vast majority
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Network Inference https://www.umu.se/en/ucmr/ec-postdoc-programme/ncrna_net-development-of-a-novel-approach-to-lncrna-mrna-regulatory-network-inference/ 7. Virome–vector competence shifts: How mosquito
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addresses subsurface uncertainties and evaluates commercial viability, promoting regional awareness and policy development for strategic alignment with regional and governmental priorities in relation to Net
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calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by Heriot-Watt University. Detailed Description We are looking for a PDRA to complete the work
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-dimensional probability, concentration and functional inequalities ? Mathematical aspects of machine learning and deep neural networks ? Free Probability aspects of Quantum Information Theory. While excellent
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. The appointment is for one year, renewable for a second year given the availability of funds. The focus is on fundamental properties of simulated neural networks, like neural scaling laws, as they manifest in
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from