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existing omics and machine learning-based pipelines to process and postprocess this data. The Project Assistant will be encouraged and given the opportunity to lead their own project analyzing proteomics
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
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to measure these backgrounds in data. The project also aims to explore to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal vs background discrimination
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. The position is linked to a research project (through WISE and WASP ) in collaboration with experts in both machine learning and artificial intelligence (Pawel Herman at KTH’s Department of Computer Science and
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methods relying on machine learning, artificial intelligence, or other computational techniques. Duties The position includes research, teaching and administration. Duties includes conducting research
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applying deep learning and/or machine learning models to medical imaging data. Other information This is a permanent position, 100 % of full time. Starting date in October 2025 or according to agreement. How
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intelligence, robotics, machine learning, and human-robot interaction. Project Description The focus of the project is artificial intelligence (AI) and its relation to robotics and embodiment. Embodiment plays a
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analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments
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neural networks / machine learning. After the qualification requirements, great emphasis will be placed on personal skills. Target degree: Doctoral degree Information regarding admission and employment