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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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, computational neuroscience, bioinformatics, robotics, or a related field Strong expertise in computational data analysis (e.g., behavioral analysis, signal processing, or machine learning) Experience working with
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a
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Website https://jobs.vhir.org/jobs/7377061-postdoctoral-researcher-stroke-research Requirements Research FieldBiological sciences » BiologyEducation LevelPhD or equivalent Skills/Qualifications Education
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- 4 Additional Information Eligibility criteria • Experience in computer modeling and programming • Knowledge of associative learning at both the neurobiological and psychological levels • Experience
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
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positions in the area of Artificial Intelligence (AI) and Machine Learning (ML) in Drug Discovery. This is a unique cluster hire initiative spanning the College of Pharmacy, Life Sciences Institute (LSI), and
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research on the boundaries between Knowledge Representation, Machine Learning and Statistics. The main purpose of a postdoctoral fellowship is to provide the candidates with enhanced skills to pursue a
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assessment, programming and machine learning. If so, we encourage you to apply! You will develop exposure and physical vulnerability maps for past and future (1970-2100) and integrate these into a flood risk
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction