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the NIH Center to iteratively refine learned models. Qualifications: • Ph.D. in applied mathematics, computational science, statistics, machine learning, or related quantitative field. • Proficiency with
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impairment across tissues and brain regions. The ideal candidate will have a quantitative background (bioinformatics, computational biology, biostatistics, statistics, computer science, or applied mathematics
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environmental trade-offs. Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems. Design and apply mathematical optimization models, including
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. Yves LE TRAON, Director of the Interdisciplinary Centre for Security, Reliability and Trust (SnT) Email: Your profile A PhD in Computer Science, Engineering or Applied Mathematics with over 15 years
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, biomedical engineering, applied mathematics, or related field. Working in team science. Desired Qualifications* The ideal candidate will have demonstrated experience in physical modeling of biological systems
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master's degree in agricultural or environmental economics, applied mathematics, or a related fieldGood background in bio-economic modelling, CGE modelling, and optimization techniquesExperience with
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master's degree in agricultural or environmental economics, applied mathematics, or a related field Good background in bio-economic modelling, CGE modelling, and optimization techniques Experience with
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. Thorough knowledge of statistics, applied mathematics, bioinformatics, or related field. Theoretical knowledge of research function in Computational Biology, Genomics, or related scientific discipline
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the workpackage team and collaborating with partners across Europe: data sharing, code exchange, joint publications. Your qualities You hold a PhD (or near completion) in statistics, applied mathematics, data
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, computer science, or applied mathematics, and superb computer programming skills. Recommended skills include an advanced command of Python and a language in the C family. Ability and a strong desire to work in a