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Field
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performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior Alpha Monetization. Blend quantitative
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of applicants Applicants must have qualifications corresponding to a master’s degree related to the subject area of the project, e.g. computational biology, bioinformatics, or statistical genetics. Please note
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statistical analyses, strong understanding of the strengths and weaknesses of scientific research and / or experience of qualitative research. Expertise will be gained in how to design and conduct a clinical
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: TRR408-A7 Investigators: Prof. Dr. Ostap Okhrin, Chair of Econometrics and Statistics esp. in the Transport Sector and co-supervised by Prof. Dr. Kai Nagel, Chair of Transportation System
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within agricultural systems experience in statistical analysis of research results or willingness to acquire such as well as to complete a PhD degree self-motivated, independent and responsible working
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aerosol inlet and a FUSION CIMS to analyze the particle-phase organic composition onboard the Zeppelin from 2027 onward Analyze large multi-dimensional datasets using statistical tools such as positive
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for pharmaceutical and biotechnological use. The ideal candidate profile: Must-have: MSc degree in the fields of biophysics, soft matter physics, physical chemistry, computational chemistry, statistical mechanics
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Operations Management Department invites candidates to apply for a 2-year postdoctoral position. We are seeking a highly motivated Postdoctoral Researcher to join our team working on Statistical Learning and
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subsurface leaching into groundwater within agricultural systems experience in statistical analysis of research results or willingness to acquire such as well as to complete a PhD degree self-motivated
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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data