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the areas of conservation biology, population ecology, ecological genetics, community ecology, evolutionary applications, or wildlife management research, focusing on mammals, birds, reptiles, amphibians
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Framework Programme? European Union / Next Generation EU Reference Number 2025-2026_3_289 Is the Job related to staff position within a Research Infrastructure? No Offer Description The HiTech BIO IAC3
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Proposed topic “Creating a National Digital Twin for self-harming
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Deadline 24 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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computer and applicable software to create databases, perform statistical analysis, present data, and perform other computer related tasks. Ability to multitask and work cooperatively with others. Strong
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Position Details Position Information Job Title Small Fruit Breeding Program - Blueberry and Strawberry Appointment Type Student Employee Job Location Corvallis Position Appointment Percent 100
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Applications are invited for a Research Scientist to join the Laboratory of Dr Quince in the Food, Microbiome and Health programme at Quadram Institute Bioscience (QIB), based in Norwich, UK. The
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
background in microbial genomics, evolutionary biology, bioinformatics, or computational biology, with an interest in translational applications that connect bacterial evolution to clinical impact. Experience
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The University of Oulu is a multidisciplinary, international research
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an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning. Work plan: Review of the state of the art in Machine Learning and Deep Reinforcement Learning