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partners in Denmark. Your primary research and tasks will be to: Assist in fish feed formulation and feed production Plan and complete in vivo studies with salmonids Conduct relevant laboratory analysis
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/or immunology. Analytical skills and some experience in statistical and bioinformatical analysis. Strong written and oral communication skills in English. Ability to work in a team and to assist
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research sections spanning the science disciplines mathematics, statistics, ML, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new
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architectures applied to molecular data. Publish scientific papers and present research results in top machine learning conferences such as NeurIPS, ICML, UAI, and AISTATS. Assist in machine learning teaching and
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, patient data are sensitive personal data to which there is only limited access, which can be a significant roadblock for researchers and students. Many promising methods to creating synthetic data based
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) for ongoing lab projects. The candidate should have a two-year master’s degree in Bioinformatics, Computational Biology, Biostatistics or in a related quantitative field (e.g. Mathematics, Physics, Statistics
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, diversity, empathy, and teamwork. You will have a great opportunity to build strong networks with internationally known researchers at DTU and other universities as well as industrial partners. You will be
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11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing
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statistical methods; Code implementation and validation for these models in a modelling setting for alternative design and policy analysis. Collaborate with researchers from machine learning and transportation
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Researcher Sumesh Sukumara (as a Main Supervisor). Additionally, you will be interacting with the Bio Digitalization and Data team under the supervision of Assistant Professor Marjan Mansourvar (as a Co