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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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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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, 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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, 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
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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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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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develop AI in scientific research in the context of DIVSOL. The candidate will also interact with various support services, e.g., research software engineers. In addition, the candidate will actively
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the context of DIVSOL. The candidate will also interact with various support services, e.g., research software engineers. In addition, the candidate will actively contribute to teaching and administrative tasks