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for the position. A solid background in synthetic organic chemistry is mandatory. The successful candidate must have experience with a broad range of synthetic and analytical methods. Experience with design of
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(written and spoken) The successful candidate is expected to move to Bergen Desired Qualifications: Experience with Stata Experience with causal inference methods, survey design, and/or machine learning
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inorganic synthesis chemists, spectroscopists, computational chemists and enzymologists. The resulting design principles will be used to develop new catalysts with rationally designed functionality. CUBE is a
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for the scalable design, processing, and deployment of DPPs. The advertised PhD position focuses on developing ML-based and distributed data processing approaches to address issues of incomplete or redundant
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ptarmigan, black grouse and capercaillie populations. This will be done through a properly designed large scale randomised controlled experiment, making the study exceptionally useful in terms of drawing
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
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period During the first months of the appointment, the successful candidate is expected to prepare a plan for the progress of the work towards a PhD degree, with a view to completing a doctorate within the
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good opportunities to develop your career and your academic skills Career guidance throughout the entire PhD program, where we work with you to develop a career plan outlining the skills and knowledge
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Forecasting (CGF) at NTNU. CGF is a centre for research-driven innovation and is funded by the Research Council of Norway and industry partners. The immediate leader is Head of Department. Duties
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Forecasting (CGF) at NTNU. CGF is a centre for research-driven innovation and is funded by the Research Council of Norway and industry partners. The immediate leader is Head of Department. Duties