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Position Description The Department of Physics at the Faculty of Mathematics and Physics, University of Ljubljana, invites applications for a postdoctoral position in the Nonequilibrium Statistical
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, applied mathematics, or a closely related discipline, with previous experience in statistical and machine learning methods and knowledge in basic biology. Applicants close to completion of their PhDs will
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Job Description Required Qualifications: (as evidenced by an attached resume) PhD, MD, or MD/PhD (or foreign equivalent). At least one academic degree in the field of Mathematics, Physics, Biomedical
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for analysing movement and behavioural data. Strong knowledge of statistical analysis, experimental design, and reproducible computational research. Experience with scientific Python libraries (NumPy, SciPy
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of mathematical statistics. You publish internationally and give lectures. You apply for projects and raise third-party funds. You hold courses independently within the scope of the provisions of the collective
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should hold a PhD (or be close to completion) in a relevant analytical and quantitative discipline, such as civil or transport engineering, transport modelling, mathematics, statistics, data science
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD, MD, or MD/PhD (or foreign equivalent). At least one academic degree in the field of Mathematics, Physics
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Qualifications PhD in Mathematical Economics and Social Science Candidates should have experience in at least one of the following areas: Statistical programming and data analysis using R, Python, or Matlab
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Population Health, Mathematics, Statistics, Computing, or a related subject, alongside demonstrable experience working with large scale datasets. Proficiency in the use of statistical programming languages and
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods