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involves collecting clinical data on the effects of childhood cancer treatment, bioinformatically handling sequence data and developing prediction models, as well as conducting Single Cell RNASeq studies and
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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to act in accordance with the university’s policies on equal opportunities and data protection. Other Qualifications You must have at least 240 higher education credits (ECTS), of which at least 60 credits
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-supervision from Professor Fredrik Tufvesson. The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is
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to agreement. As a PhD student you will be enrolled in a highly qualified education within a thriving research environment. For more information about our PhD program, please visit our information page. You will
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theses and publications (if any). Names and contact information of at least one reference person. You apply via our e-recruitment system Varbi. The deadline for applications is September 30, 2025. Log in
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, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
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information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Name of research project
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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Experience with performing laboratory experiments Ability to work with large data sets (> 500 GB) Numerical modelling Main responsibilities Independent research and research training (80% of time) Support for