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deliverables with high standards of accuracy and clarity. Teach and supervise BSc and MSc student projects, and be co-supervisor for PhD students We are looking for candidates with: Skills in molecular biology
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operation of defined microbial communities, and modeling on metabolic interactions. Your qualifications You should have a PhD in microbiology, molecular biology, molecular genetics, or related field, and
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Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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energy system. Qualified applicants must have: PhD degree in physics, astronomy, engineering, computer science or similar. Experience with finite element modeling, ideally Comsol Multiphysics. Experience
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QGG Aarhus University seeks two Postdoctoral researchers in Quantitative Genetics of sustainable ...
tools or functional genomic information or OMICS to improve genomic prediction models. The persons hired will collaborate with industry partners, teach at undergraduate and graduate levels, and supervise
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essential. Familiarity with paleoclimate data or experience adapting models to data-limited contexts would be a significant advantage The PhD must be obtained within the last 8 years The successful candidate
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are looking for a highly motivated, innovative, and collaborative postdoc to lead research projects on centrosome and cilia biology as outline above. You have: A PhD in life science, e.g., molecular biology or
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validation in rodent migraine models Close collaboration with computational protein engineers and clinical researchers Data analysis, manuscript preparation, and supervision of students where relevant
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diagnostic pathways. Core research tasks include planning, conducting and publishing epidemiological studies using large-scale observational data, primarily register-based, with a focus on effects of ADHD