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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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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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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
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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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through the application of both well-established statistical modelling and newer machine learning methods. The research specialist will be integrated in the computational team led by John Wallert
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spatial mass spectrometry. Experience with single-cell omics is also an advantage. Advanced biostatistics and machine learning, such as multivariate analysis, regularization, deep learning, or network
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criteria for the specified third cycle studies. Specific knowledge in machine learning, data analytics, sector-coupling and Mixed-Integer Linear Programming (MILP) is a merit. In addition to the above, there
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to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal vs background discrimination. This will become more of a focus later in the project. Beyond
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of neurodegenerative disease. Familiarity with fMRI processing software (fmriprep, CuBIDS, XCP). Expertise applying deep learning and/or machine learning models to medical imaging data. Other information This is a
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dynamics, targeting large-scale systems equipped with GPUs and other accelerators. Key research topics include mixed-precision numerical methods, integrating machine learning into computational workflows