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approaches in postharvest management and highlight the need for further fundamental and exploratory research at the interface between postharvest science and data-oriented analysis. Objectives: Advance
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learning, computational biology, and AI for science The postdoc will work at the interface of machine learning, genomics, and scientific computing, contributing both methodological innovation and
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candidates in all areas of Biomedical Engineering are encouraged to apply, with strategic interest in: Bioelectronics Brain-Computer Interfaces Biomaterials and Biomanufacturing Organoids and Organ-on-a-Chip
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scientific publications. Where to apply Website https://www.academictransfer.com/en/jobs/359131/phd-process-intensification-for… Requirements Specific Requirements A master’s degree (or an equivalent
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PhD in Statistical Science, two MS degrees (Biostatistics and Statistical Science with concentrations in Modern Statistics and Statistical Data Science), a BS in Statistics with four concentrations, and
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PhD Studentship in: Water and Vegetation Driven Failure Modes on Railway Infrastructure School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded Students Worldwide
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by Supervisor. Job Requirements Master/PhD in Naval Architecture, Ocean Engineering, Marine Engineering, Civil Engineering, or related field. Proficiency in hydrodynamic modeling tools (e.g., ANSYS
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of the fabricated samples. Research will be conducted in collaboration with PhD students and members of the Orsay group, using the expertise and manufacturing capabilities of the LPS as well as the neighbouring C2N
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://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed by the team: https
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expertise/interest in Bayesian methods for addressing measurement error. Ideally PhD within the last 5 years. Advanced level experience with R, desired knowledge of Nimble, Overleaf. Excellent communication