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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
resistant and susceptible plants. Develop an AI-assisted image-based phenotyping pipeline to automatically quantify aphid performances on the plants. This software will automatically count for aphids and
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software and machine learning techniques for advanced image-array data analysis. Achievement of the expected progression within Post Doc and Senior Post Doc is transferable between the Irish HEI’s. This can
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resistant and susceptible plants. Develop an AI-assisted image-based phenotyping pipeline to automatically quantify aphid performances on the plants. This software will automatically count for aphids and
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Term: Initially 1 year, renewable. Appointment Start Date: As early as March 2026, but flexible Group or Departmental Website: https://med.stanford.edu/bridge-lab.html (link is external) How to Submit
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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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, 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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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