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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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that yield valid statistical conclusions (inference) on causal effects when using machine learning algorithms and big datasets. The project is part of the research environment Stat4Reg (www.stat4reg.se ), and
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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molecularly and genetically based treatments. Eligibility requirements Applicants meet the basic eligibility requirements for doctoral studies if they have: Completed a second-cycle (Master’s level) degree
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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providing interaction with researchers from diverse research fields and access to various scientific and technical expertise. Background and description of tasks We are developing genetic screening tools
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; 45 credits in the major areas of biology or molecular biology with at least 7.5 credits in genetics and 22,5 credits in the fields of microbiology, physiology and cell-and molecular biology