98 algorithm-development-"Multiple"-"Prof"-"Prof"-"Newcastle-University" Fellowship positions at Nature Careers
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foundation to: Build a high-impact research portfolio Deepen expertise at the intersection of AI and science Develop strong international academic and research networks Accelerate the transition to tenure
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meetings. • Develop independent research questions that align with the division's mission. • Mentor students and junior research staff, as appropriate. Required Qualifications: • Ph.D. or M.D./Ph.D. in
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., somatic) somatic mutations in the human brain. The lab is interested in studying somatic variation as it pertains to typical brain development as well as in neurological diseases like epilepsy. To that end
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safety, health, and cultural and social acceptance. We will enable the development of a more holistic, efficient and safe approach to new food and drugs and related technologies, as exemplified by advances
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2-year Postdoctoral Research Fellow position with focus on Cryptography at Computer Science Aarhu...
informed of the latest developments in the field. Required Qualifications Ph.D. in computer science. Interest in developing and evaluating cryptographic protocols and their applications. Knowledge of state
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environment (English as working language) Workshops and training for career development Requirements All research fields supported at ISTA will be eligible (see https://ista.ac.at/en/research ). At the date
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. Dr. Wang's laboratory conducts cutting-edge research to understand the evolution of cancer transcriptomes through DNA-RNA dynamics, aiming to uncover mechanisms of cancer initiation, progression, and
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the lab Develop AI-powered pipelines for analysis of microendoscopic calcium imaging, confocal fluorescence microscopy, and behavioral videos Lead cross-modality image registration applications Launch new
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lead the in vivo functional analysis of this gene using conditional KO mouse models, with a focus on brain development, neuronal differentiation, and seizure susceptibility. All models are already
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possible thereafter. The aim of this project is to advance the development of multi-trait Bayesian linear regression models that enable the sharing of genomic information across traits and biological layers