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research project within finance. The course part of the doctoral education amounts to 90 ECTS, while the research (thesis) to 150 ECTS. As a doctoral student you are expected to contribute to the research
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develop privacy-aware machine learning (ML) models. We are interested in building models that are explainable and are extracted from complex and heterogeneous data. Within explainable ML, we are interested
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to be full-time starting on 2024-09-01 or according to agreement. You who are admitted to doctoral education will be part of the faculty-wide doctoral training program at the Faculty of Medicine
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develop your skills and contribute to mathematical machine learning research. The assessment of applicants is based on their qualifications and ability to benefit from the doctoral study they will receive
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and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.1 billion SEK
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Applied Physics with a focus on biomedical engineering. The project is focused on magnetic resonance imaging (MRI) measurements in neurological applications with the aim to develop and evaluate new
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to solve a problem. Our project goal is to design and develop interactive systems that reason spatially and which are centred in the human user (e.g. to expand their skills, instead of replacing them
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requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad, or equivalent qualifications. The candidate should have
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ethylene, and to further develop the system to reach the 12000 cm-1 energy levels in methane. The data obtained in the project will allow the verification of the theoretical predictions of high-temperature
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the doctoral education they will receive. About the employment The position is intended to result in a doctoral degree. The main task of the doctoral student is to pursue their third-cycle studies, including