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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD in physics or engineering sciences. He/she should have an experimental profile and demonstrate a strong
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QUALIFICATIONS PhD in Ecology, Geography, Environmental Science, or a closely related discipline. Demonstrated specialization in remote sensing and spatio-temporal environmental data analysis. Strong programming
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate
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the day) to accommodate your needs. Working remotely is possible for up to 1 day/week. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus, Oxford
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in-person on campus at Princeton University. Applicants must apply online at https://puwebp.princeton.edu/AcadHire/position/40541 and submit a CV, cover letter, and contact information for three
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: Compiling and analyzing large erosion data sets (thermochronology, cosmogenic nuclides, suspended sediment, etc.); Statistical modelling of data to analyze drivers and make local and/or global predictions
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JOB SUMMARY The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience