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. -Contribute to general laboratory maintenance. -Other duties as required Required Education: -PhD in Molecular Biology or related field. Preferred Experience: -Working with plants and insect vectors of plant
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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Science Partnerships Fund Early Career Fellowships programme, delivered by the British Council. The International Science Partnerships Fund puts research and innovation at the heart of our international
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about our areas of interest can be found in the group website. Applicants must have (or be about to receive) a PhD in Physics, Chemistry, Materials Science, or a related subject. The ideal candidate will
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training and research. MINIMUM QUALIFICATIONS PhD in neuroscience, neurobiology, machine learning, biomedical engineering, or related field. Demonstrated experience independently executing all phases of a
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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journals, and have the chance to participate in national and international schools and conferences. Profile You have a PhD degree in Physics, Computational Science, or equivalent qualification. Exceptional
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experience: Essential criteria PhD in computer science, AI or related area Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
. We conduct research in all areas of modern chemistry, and our research program is one of the strongest in the country with more than 300 publications annually and over 100 patents filed within the last
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candidates to pursue postdoctoral studies (i.e. PhD). The CAMB MOM study conducts multiomics analyses (lipidomics, metabolomics, proteomics, and transcriptomics) on samples from a cohort of breastfeeding