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at Uppsala University can be found here . Project description Digital pathology and detection of cancer based on hematoxylin and eosin (H&E) stained tissue samples has made enormous progress in
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rate, and virtually nothing is known about a putative connection between these mutation rates. Using several Drosophila melanogaster model systems, in combination with quantitative genetics, experimental
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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
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modeling of magnetic materials using first-principles methods. Good knowledge of programming is required. Meritorious experience for the position is demonstrated knowledge of Git, Python, Bash and VASP. Good
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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immunity and develop diagnostic approaches that accurately predict therapy benefit and enable successful individualized cancer therapy planning. Contemporary AI-based approaches show great promise to advance
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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plasma model (www.amitiscode.com ). By comparing model results with NASA’s MESSENGER and ESA’s/JAXA’s BepiColombo observations, the research aims to deepen our understanding of Mercury’s magnetosphere
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, science, and, yes, the occasional laugh over fika ☕️.This is not your average PhD position – it's a unique opportunity to shape the future of AI-based 6G wireless communication, contributing to world