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Interfolio to: https://apply.interfolio.com/176454 The review of credentials will begin immediately and will continue until the position is filled. Equal Employment Opportunity Statement For people in the EU
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
. Proficiency in at least two of the following programming languages: Python, R. Experience in Machine Learning and Computational RNA Biology are desirable. Hands-on experience or understanding (the limitations
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periods for learning, and how individuals’ innate variations interact with experience to give rise to differences in learned behaviors. The team focuses on vocal learning in songbirds as a model system to
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of results. Highly motivated and have good communication, project management and organisational skills. Willing to learn new skills and techniques. Desirable Experience in proteomics and cancer models would be
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materials. Experience with the use of machine learning or artificial intelligence is desirable but not required. This search is part of UC Davis’ commitment to hiring leading research faculty with a strong
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looking for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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clinical trials, advanced computational methods, neuroimaging, brain stimulation, body-machine interfacing, gamification of therapy, assistive technology design, development and evaluation, outcome measure
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, networks and communication systems, theory of computation, computing paradigms, AI and machine learning, numerical computing, and applied computing. In particular, beyond surveying individual fields and
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dynamics, kinematics, acoustics/vibrations, fluid–structure interaction, control, or other mechanics-driven domains. Experience with applied computational methods and machine-learning–based modeling
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and other multimodal datasets Design and fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior Collaborate closely with experimentalists