180 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions in United States
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limited to: learning technology, information, language, and computing technologies to advance learning, training, cognitive development, and human performance. Position Overview Provides ongoing mentorship
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@duke.edu. Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic
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molecular biology, biochemistry, cell biology, genetics and immunology. We are broadly interested in exploring how the host defends against invasion of pathogens including viruses and bacteria, and in
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neurophysiological recordings, imaging studies, and behavioral experiments Present research findings at internal seminars, external conferences, and scientific meetings Actively engage in the Neuroscience PhD Program
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. Experience: Conducting field, computer, web-based, and interpersonal interaction-based experiments. Preferred Competencies Familiarity with methods of experimentation. Implement creative and innovative
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applications as Principal Investigator or Co-Investigator Preferred Qualifications: Ph.D. in molecular biology, genetics, biochemistry, cell biology, or a related field Demonstrated record of publication in peer
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, atypical cellular or blood trait, genetic information (including the refusal to submit to genetic testing), or any other category protected by law. As an institution, we value diversity of background and
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T cell plasticity and reprograming. The laboratory is part of the Lombardi Comprehensive Cancer Center (LCCC), a multidisciplinary research center focusing on cancer, genetics, metabolism and immune
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, computer science, bioinformatics, or o ther related disciplines is required. Strong interest, research background and experience in the methodology research in functional data analysi s, tensorregression, high
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, which has seen little improvement in patient survival over the past decades. Utilizing genetically engineered mouse and human glioma models, our lab investigates how glioma cells interact with the tumor