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independently to develop therapeutic agents against mutant p53 and other oncoproteins using artificial intelligence, monoclonal antibodies, and DNA vaccines. The positions offer a unique team-based science
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to keep the data up-to data with very little effort. Estimate energy and land needs for the realization of the CCU potential. Develop a multi-objective optimization model for individual CCUS projects
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. Project overview The project involves applying advanced statistical analysis, machine learning techniques, and modeling approaches such as agent-based modeling to analyze diverse climate and socioeconomic
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. The models will be based on eco-evolutionary theory and informed with ecological and evolutionary data from public databases and published papers. This combined theoretical and data driven approach includes
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/w) fixed-term postdoctoral position in Simulation and Modelling. The position focuses on designing and implementing the agent-based modeling component of research projects in code, requiring
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. Construct machine-learning models for feature-based molecular property prediction and drive the inverse design of ligands with engineered properties. Develop machine-learned interatomic potentials trained
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agreement (preferably, 2025 Q2) Duration: 1 year, renewable based on performance and funding availability About the Position We are seeking a highly motivated Postdoctoral Researcher to lead research
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Applications Starting date: Upon agreement (preferably, 2025 Q2) Duration: 1(+1) years, renewable based on performance and funding availability About the Position We are seeking a Postdoctoral Researcher to
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and conducting experiments using various mouse models of disease. This position involves investigating how bacterial agents modulate immune responses to develop novel therapeutic strategies, with a
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, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be