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algorithms and data structures, and solid programming skills. A background in one or more of: machine learning, reinforcement learning, combinatorial optimization, operations research, or distributed systems
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biological and medical research questions. Strong expertise in (Bayesian) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies
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integration, etc.. Participation in these projects will include scientific programming, data analysis, manuscript preparation, meeting with collaborators, etc.. Minimum Qualifications A Ph.D. in computer
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mesocosm experiments. You will be measuring greenhouse gas fluxes using advanced methods for gas detection in the field and laboratory, including stable isotope techniques, and deploy mathematical and
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background in communication and transport network design, with demonstrated expertise in network resilience or survivability and in network optimization. Solid programming skills (for example in Python) and
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defined by protected attributes (e.g. gender, age, ethnicity, …). Theoretical relations between fairness notions: studying the mathematical relationships, trade-offs, and impossibility results connecting
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bioinformatic and analytic aspects of predictive modeling. MINIMUM JOB QUALIFICATIONS: A Ph.D. in bioinformatics, genetics, statistics, mathematical, physical, or computer science, or comparable research
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positions are set out in the Regulations relating to the Act relating to Universities and University Colleges . It will be an advantage if you have Documented strong competence in programming, for
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particular statistical physics, dynamical systems and stochastic processes, together with strong numerical and programming skills. Prior knowledge of soft condensed matter, phase separation or cellular biology
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field, or be in the final stages of PhD submission. Strong scientific programming skills in Python. Knowledge of mathematical models of biological systems and numerical methods for differential