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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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, including public policy and administration, comparative politics, political theory, international relations and research methods. The appointment is for a fixed, non-tenured term of 4 years, and has a 25
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din. En cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en
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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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USN’s PhD-program in Technology within three months of accession in the position. About the PhD-project The build-up of CO2 in the earth’s atmosphere is recognized as the single most important
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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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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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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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defence of your doctoral thesis is a prerequisite for employment. In addition to your PhD, it is an advantage if you have: experience with ocean numerical model systems, such as the Regional Ocean Modelling