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. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining
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. The committee's mandate is to undertake an assessment of the applicants' qualifications based on the written material presented by the applicants, and the detailed description draw up for the position. A copy of
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technology. The planned work is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in collaboration with a non-profit
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microscopy. Experience with cancer organoid models and/or bioinformatics is an advantage. We offer broad training possibilities in the required experimental methods within a stimulating academic environment in
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presented before taking up the position. CV A copy of the doctoral thesis. If you are close to submitting, you can attach a draft of the thesis. A project sketch containing proposals for an overall
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guidelines . CV A copy of the master thesis and, if applicable, a list of other scientific publications. 2-3 personal references including contact information and relation to the applicant Copy of education
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presented by the applicants, and the detailed description draw up for the position. A copy of the assessment report will be sent to all applicants. The applicants who are assessed as best qualified will be
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to develop a PhD project within the frame described in the call and the project description (available on request). All applicants should carefully read the Faculty guidelines . CV A copy of the master thesis
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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multiwavelet methods in our code (MRChem), and in particular in connection with recent developments for real-time simulations and correlated methods. This development will then be connected to the computation