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in this project. Additionally, the student will be encouraged to collaboratively contribute to the further development of these methods. The PhD student will be supervised by Academy Fellow Dr. Gleb
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collection and/or experimentation. We seek candidates who have completed a PhD in ecology or a related field, have strong conceptual and statistical skills, and experience working with large and complex
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on the research interests of the candidate, there will also be opportunities to complement existing data with additional field data collection and/or experimentation. We seek candidates who have completed a PhD in
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, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug development. The successful candidate will contribute
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participate in a project which investigates and develops novel immunotherapies (cell therapies) to cancer, utilizing both mouse and human systems. Applicants should possess a PhD degree or be close to
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drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
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drylands, and other pressing environmental issues. You will gain experience in working at unique research sites in iconic East-African savanna landscapes and learn about the state-of-the-art methods in
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using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
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degree (PhD or equivalent) in computer science, data science, statistics, bioinformatics, or a related discipline A strong publication record in machine learning, computer science, bioinformatics
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy