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Field
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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Sequencing (GBS), Whole Genome Sequencing (WGS) and targeted genotyping chips (e.g. MassArray) and analyze them together with environmental data using population genetics and machine learning tools
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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focused on understanding and countering harmful narratives and, mis/disinformation, and applying social network analysis. To be successful you will need: PhD in a relevant discipline such as computer
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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, along with a strong theoretical or practical background in statistical mechanics, quantum dynamics, or Machine Learning. Demonstrated experience operating and maintaining a research codebase and data
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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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. Minimum Requirements: The position requires a PhD in biological sciences, chemistry, or a related discipline and a strong record of publications in peer-reviewed journals. Preferred Qualifications: Ideal
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-edge machine learning, including Large Language Models (LLMs), to enhance decision-making and planning in robotic systems. Qualifications: Applicants must have a PhD in Robotics, Control Theory
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Experience with molecular biology techniques and cell culture Willingness to learn new techniques and skills Ability to independently design and conduct experiments Willingness to think critically A passion