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Field
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will have the opportunity to work closely with our engineers and other research staff. Projects may include software package creation and maintenance, data engineering, development and/or implementation
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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approaches such as Life Cycle Assessment. You should also have experience of analysing research results in a transparent and reproducible way, using relevant tools and software. You should be enthusiastic
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is available here: https://acrobat.adobe.com/id/urn:aaid:sc:VA6C2:b74beba8-716f-4ab4-b791-2fb6c087ca7f Job Requirements REQUIRED: Ph.D. in neuroscience, biomedical engineering, chemical engineering
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, DLS, DSC, TGA, DMA, AFM, rheology, adhesion testing, FTIR, Raman, or comparable methods Evidence of scientific output (e.g., peer-reviewed publications, preprints, patents, software, industrial reports
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/optical ray tracing simulation software, e.g., Wireless Insite, Zemax Proven track record of publications in relevant IEEE journals and conferences The candidates will be considered until the position is
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intensive and has a strong tradition of research-led teaching. The School offers undergraduate majors in computer science, information systems, data science and software development within its flagship
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biology, and evolution. Learn more about our interests, motivations and discoveries: https://sites.duke.edu/silverlab/ . Conduct independent research activities under the guidance of a faculty mentor in
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 months ago
accurately study the selected algorithms, participate in the development and maintenance of the PEPit (https://pepit.readthedocs.io/ ) and AutoLyap (https://github.com/AutoLyap/AutoLyap/ ) software packages