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. The researcher will develop novel research that applies advanced data science, machine learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling
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Postdoctoral Associate - Sustainable Energy and Synthetic Biology The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and Cornell University’s second largest
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Position Details Position Information Recruitment/Posting Title Postdoctoral Associate Job Category Staff & Executive - Research (Laboratory/Non-Laboratory) Department CINJ - Medical Immunology
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May Substitute For Minimum Education. Certifications/Professional Licenses: No specific certification/professional license is required for this position. Work Experience: Postdoctoral (3 Years) Skills
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 10 days ago
candidate is expected to teach can be found here: https://www.cs.utoronto.ca/~trebla/CSCB09-2025-Summer/ . The successful candidate must demonstrate thorough familiarity with the course material. Previous
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About the Opportunity This postdoctoral position offers an opportunity to conduct leading-edge research in embedded security with applications to healthcare and medical device cybersecurity
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Biology, Biology, Machine Learning, Statistics, Medicine, Physics, Chemistry, Engineering, Mathematics, Computer Science, or other related fields) coupled with direct experience in computational research
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. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with an emphasis on pattern identification, prediction, or spatial risk mapping
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/erapid-multiplexed-electrochemical-sensors-for-fast