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of postdoctoral associates, PhD students, and several Master’s or undergraduate students across multiple universities and organizations. The research team will work alongside the engineering team to investigate
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. Swindler Chemical and Biological Engineering Physical Location of Position (City) Rapid City Posting Text The Karen M Swindler Department of Chemical and Biological Engineering (CBE) at South Dakota Mines
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of working in interdisciplinary contexts (desired) Our Offer The PhD position is awarded for three years, with the possibility of an extension of 12 months (pending a positive evaluation). Employment will be
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Max Planck Institute for Social Anthropology, Halle (Saale) | Halle, Sachsen Anhalt | Germany | 19 days ago
(desired) experience of working in interdisciplinary contexts (desired) Our offer The PhD position is awarded for three years, with the possibility of an extension of 12 months (pending a positive evaluation
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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substantial experimental components that should be published in peer-reviewed international journals and at major conferences. The position will include supervision of PhD and MSc students, teaching and
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upon genetic results. Techniques used: you will be trained in a large variety of techniques including epidemiology, statistical genetics, in silico data mining, cell culture including CRISPR-based genome
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to academic leadership. Renowned for his work in Big Data and healthcare innovation, Dr. Madigan has authored over 200 publications covering topics such as Bayesian statistics, text mining, and probabilistic
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and control of windfarms For this position the research activity is expected to develop new methods in robust and physics-informed machine learning, reduced-order modelling, data-driven nonlinear model
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for selecting, curating and mining publicly available datasets for novel cancer-specific antigens, employing in-house methods and to develop new pipelines to integrating data generated on multiple platforms (i.e