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cells Key methods will include: Gaussian Processes (heteroscedastic & multivariate) Operator-valued and deep kernels Active Bayesian experimental design Physics-informed neural networks Closed-loop
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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approaches—GAMs, Random Forest, boosted models, and multivariate methods—to quantify habitat associations, map species–environment relationships, and identify high-priority conservation areas, including
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. Serves as primary coordinator between University, non-Yale collaborators, pharmaceutical companies, HIC, IRB and funding sources. Performs descriptive and multivariate statistical analyses of data, using
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. Thus neuronal experimental data are to be analyzed for both aspects by PCA analysis and statistical multivariate methods to extract spatio-temporal spike patterns. Finally both results will be linked and
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at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Study Development: Conducting literature review, designing studies
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valorization and pilot process design is a strong asset. Proven publication record and project involvement. Additional Skills (Preferred): Experience with environmental data analysis (R, multivariate statistics
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-solving abilities. Strong written and oral communication skills in both English and French. Additional Skills (Preferred): Experience with environmental data analysis (R, Python, multivariate statistics
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experience in, for example, C, C++, MATLAB, or Julia would be a plus Data visualisation Bash scripting in a Linux environment, ideally tailored to an HPC infrastructure Multivariate statistics Containerized
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, Information Technology, Intelligent Systems Engineering, Network Engineering and Security, and Software Engineering. Find out more about SoC at https://www.cdm.depaul.edu/academics/Pages/School-of-Computing.aspx