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academic and professional qualifications Proven research experience in the field of modelling and analysis of biological networks Solid foundation in mathematics and algorithmic design Strong programming
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, Illinois 60612, United States of America Subject Area: Mathematical and Computational Biology Appl Deadline: 2025/06/30 11:59PM (posted 2025/02/04, listed until 2025/06/30) Position Description: Position
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data, metabolomics and/or proteomics. Develops robust pipelines for data annotation, analysis, and quality control. Creates analytical algorithms and tools to address scientific questions with big data
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Job Description Join the Multi-omics Network Analytics Research Team as a Postdoc in Computational Biology at the Danish Technical University (DTU) Are you an experienced scientist with a passion
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these issues. The center brings together experts on climate impact research and process-based modelling of biogeochemistry, agronomy, biology and geography from Aarhus University and University of Copenhagen, as
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of the Austrian Academy of Sciences. Selected candidates will join one of CeMM’s research groups for 3 to 6 years, addressing ambitious research questions in areas such as cancer, immunology, chemical biology
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these issues. The center brings together experts on climate impact research and process-based modelling of biogeochemistry, agronomy, biology and geography from Aarhus University and University of Copenhagen, as
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Number: JR88866 Position Summary The Marti Lab in the Department of Cell Biology & Physiology builds next-generation imaging and AI tools to reveal how health, aging, and disease progress inside living
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 9 days ago
: · PhD in Mathematical Biology, Ecological Modeling, Economics, Fisheries Science, or a related field. · Strong background in ecological and/or economic modeling, population dynamics, and quantitative
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted