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- AALTO UNIVERSITY
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, including members specialising in biology, microfluidics, machine learning and clinical research from RMIT University and Leading Technology Group (LTG). LTG is an Australian group of medical research
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Max Planck Institute of Molecular Plant Physiology • | Potsdam, Brandenburg | Germany | about 18 hours ago
approach combining molecular biology, genetics, genomics, epigenomics, metabolomics, biochemistry, biophysics and microscopy with bioinformatics and modelling. We work with Arabidopsis thaliana, tobacco
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Degree PhD/Dr rer nat/Dr rer medic/Dr-Ing Course location Dresden In cooperation with International Max Planck Research School for Cell, Developmental and Systems Biology (IMPRS-CellDevoSys) under
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should hold a Master's degree or equivalent in climate or environmental science, ecology, biology, geography, or a related field. Due to the large datasets that will need to be handled from the beginning
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TV-L, part-time 65 %, limited for 3 years, start: as soon as possible) Are you passionate about machine learning, molecular science, and making discoveries at the interface of biology and chemistry
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How many positions: 1 This 4-year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free stipend set at the UKRI rate (£19,237 for 2024/25) plus an additional £3,000 provided by the...
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to benefit from training and development opportunities associated with these bodies. Entry requirements The minimum entry requirement is 2:1 in Biology, Food Sciences, Sociology, Mathematics, Statistics
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ecology with an emphasis on conservation biology. Your immediate leader will be the Head of Department. About the project The team of supervisors will consist of Ass. Prof. Kristine Bakke Westergaard (main
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qualifications Masters degree in a relavent scientific field, such as biology, ecology, or natural resource management Experience conducting field work Basic statistical competence The following experiences and
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infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good