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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
Posting Information Posting Details Department Lampe Biomedical Engineering - 424601 Posting Open Date 06/25/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar
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required) Kinetic modeling proficiency (Chemkin, Cantera), analytical proficiency (sensitivity, rate of production, etc.) Spectroscopic modeling experience preferred (HITRAN/HITEMP) Familiarity with
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statistical data related to the social class position of migrants with different legal statuses. The organisation of an international academic workshop is part of the tasks to be carried out within
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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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to the in-situ field measurements at Itatinga. The Ecotron experiments are not part of the postdoctoral work and will be made by a French PhD student. Combining data from Eucalyptus stands and
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, geospatial data), clean and manipulate them into analysis read versions. - Identify new and emerging data science techniques that will enhance project design and analytical rigour. - Planning, conducting and
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Strong analytical skills Ability to engage in community-focused service and events Minimum Qualifications PhD in Speech, Language, and Hearing Sciences, Psychology, Neuroscience, or another related field
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Postdoctoral Researcher -Discovery and Bioengineered Production of High-Value Plant Natural Products
for publication in peer-reviewed journals, presenting data at conferences, and contributing to the success of the team. Required qualifications: • PhD degree in Plant Biochemistry, Plant Biotechnology, Analytical
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models in mice. Experience managing and integrating multi-scale datasets, with knowledge of consortium-based data-sharing protocols and practices. Strong analytical skills for interpreting complex datasets
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with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis of biological