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have expertise in at least one of the following research areas: PDEs, numerical methods, optimization, functional analysis, or stochastic analysis Candidates without a master’s degree have until 1st
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motivated PhD candidate to conduct research in the field of evidence synthesis. The project will focus on statistical methods for living network meta-analyses – dynamic networks of interventions
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to carrying out a project entitled “Sequential and adaptive methods for living network meta-analyses”. The research fellow must take part in the faculty’s approved PhD program and is expected to complete
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or numerical methods in the context of environmental research is highly advantageous. Experience with the interpretation of field data is advantageous. Grade requirements: The norm is as follows: the average
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design using computational methods Organic synthesis MD simulations Knowledge of a scripting language The candidate must demonstrate a structured approach to work, a strong commitment for hit discovery and
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the following areas is an advantage: Structure-based drug design using computational methods Organic synthesis MD simulations Knowledge of a scripting language The candidate must demonstrate a structured approach
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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
, Sustainable Finance, and Twin Transition Apply for this job See advertisement About the positions Inland School of Business and Social Sciences , The PhD programme Innovation in Services in the Public and
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projects will work towards this goal. PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en
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. The successful PhD candidate will collaborate closely as part of an interdisciplinary team consisting of formulation scientists, microbiologists and computer scientists. As a PhD candidate at OsloMet, you will
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of Computer Science at UiT The Arctic University of Norway. HDL’s mission is to build and experimentally evaluate the systems, methods, and tools needed to analyze and interpret complex health datasets. The group