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strongly supported by our college-level instructional design team for course development and delivery and by our research core for grant development and submission. Dr. Jinling Liu’s laboratory ( https
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Minimum Education and Experience PhD is required along with knowledge of molecular biology, computer programming, statistical analysis and genome evolution. Mentoring experience is also required
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Psychology includes the Dean’s office, a StudyServiceCenter and four Departments (see https://univie.ac.at/psychologie) . The courses offered in Psychology includes a bachelor's, master's and doctoral
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experience in blockchain technology (preferably Ethereum) and/or machine learning. Solid foundation in computer network and/or data analysis. Strong programming skills, preferably in Java. Ability to work
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proficiency in programming (preferably Python) are essential. Prior exposure to one or more of the following: machine learning, information security, modern crypto systems will be an advantage
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funding applications will be considered an advantage. Experience in advanced statistical analyses and programming (e.g., R, Python, or related tools) is an asset. Further information on the Department
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Experience in X-ray or neutron scattering methods Experience in research related to the focus area of the project of your choice Experience with analysis of scientific data Scientific programming skills
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 5 hours ago
Further details can be found at: https://deepwave.kaust.edu.sa/research Thus, the candidate is expected to have or about to have a PhD in a relevant topic, that includes geophysics, mathematics, physics
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recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service. Premila’s research group (https://sites.google.com/view/premila
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publications can be found on his lab website: https://www.zhuhlab.com The candidates will focus on one or two of the following projects: Developing predictive toxicity models for assessing new