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should have a Master in Engineering, Physics or Chemistry and preferably a background in Statistical Thermodynamics and Molecular Simulation. Experience with programming in scientific languages such as
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Fuels. Number of positions: 2 Reference: PhD 2024-11/12 ALL Supervisor: Prof. Feliu Maseras Project: Statistical treatments for computational homogeneous catalysis. Number of positions: 1 Reference: PhD
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degree, ideally a doctoral degree in mathematical modelling, statistics, epidemiology or another relevant discipline with a strong quantitative component. Candidates should also demonstrate experience in
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the ability to conduct and complete research projects, as witnessed by published work in machine learning on the specific topics, and strong mathematical skills in probability and statistics. Good knowledge
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understanding of computational biology, probabilistic models, statistics, machine learning, and discrete mathematics. Ability to analyze and interpret large complex data sets, such as genome sequences, microarray
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department evaluates, treats, coordinates and carries out the prescribed physical rehabilitation of athletes. The position is responsible for the compilation and maintenance of medical and statistical records
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invertebrate husbandry Strong background in statistics Responsibilities: Research/experiments: Conducts research experiments. Collects data and analyzes results. Documentation and publishing: Writes manuscripts
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statistical software packages such as STATA, SPSS, SAS or R, or willing to acquire such knowledge. You pay attention to details and act with attention to quality and integrity. You have a sense of independence
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Knowledge, Skills, and Abilities: Ability to multi-task and work cooperatively with others. Knowledge of laboratory techniques and statistical procedures.** Advanced computer skills in word processing
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research trials, statistics and/or data management; knowledge of clinical research practices and longitudinal cohort studies Experience working with people living with HIV in a service or research capacity