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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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environments. Access proprietary market data and institutional infrastructure, including cutting-edge computing environments and live market simulation tools. Translate research into production, contributing
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, scientific publishing, organisation of project events and communication. The successful candidate should apply to the Doctoral Programme in Social Sciences and obtain the study right within the trial period
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component modeling and testing. Knowledge or classwork related to energy systems with design and computational model analysis using engineering software will be necessary. Demonstrated research capability and
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demonstrate suitable experience in computer science, machine learning, robotic vision, or a related field (through a high-quality Honours or Masters degree). The successful candidate must be able to enrol as a
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, and industrial partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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Researcher (R1) Country Belgium Application Deadline 30 Sep 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 38 Is the job funded through the EU Research Framework Programme
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and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture