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associated with shellfish culture. Responsibilities will include management of a breeding program for hard clams, and independent research evaluating the environmental stressors influencing shellfish
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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
platform and the evaluation of the efficacy against Marek's disease and targeted poultry disease. You will construct the recombinant Marek's disease virus that expresses the foreign antigens. You will learn
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the validity of data-processing workflows, evaluate effective tutoring moves using the MTM dataset, and share innovations and best practices for analyzing tutoring data at scale. NTO research encompasses (but is
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research studies under the direction of the principal investigator. Plans, directs, and conducts specialized and advanced research experiments. Evaluates and analyzes data. Establishes new research protocols
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experiments. Evaluates and analyzes data. Establishes new research protocols and procedures. Summarizes research findings and publish results in research journals. Minimum Qualifications MD or Ph.D. in Basic
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of detailed curriculum vitae structured according to the items under point 5; c) Other documents that are relevant for the evaluation of the qualification in related scientific areas; d) Any other documents
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% – Agricultural Data Analytics, Machine Learning, and Remote Sensing Develop, evaluate, and implement machine learning and data analytics approaches for quantifying crop phenotypic and agronomic traits. Process and
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(0.5FTE) in the Research Ireland funded COALESCE project 'Evaluation of Comprehensive Alcohol Warning Labels in Ireland': The Project and the Team: The project evaluates the effectiveness of alcohol warning
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 9 days ago
students • Participation in evaluation activities • General administrative and organisational duties Where to apply E-mail [email protected] Requirements Research FieldMedical sciences
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures