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DRIVE35 Collaborate programme, and aims to meet the evolving needs of urban populations while accelerating the shift to zero tailpipe emission transport by validating a novel, lightweight BEV in the L6e
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requirements for our PhD programme . Skills in Python, C++ or ROS are preferred. How to apply Applications should be submitted via the Robotics and Autonomous Systems PhD programme page. In place of a research
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technologies and the development of energy-efficient spintronic devices. Duties of the position Complete the PhD program within three years, including the successful completion of four mandatory courses. Carry
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to potential experimental realizations with significant impact on emerging technologies and the design of energy-efficient spintronic devices. Duties of the position Complete the PhD program within three years
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2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by
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ecosystems and global environmental change. At EMBRACER we work at the very frontiers of knowledge on climate change, Earth’s climate system and climate feedbacks. Within its 10-year research programme
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is a vibrant international doctoral program with about 75 doctoral students from more than 25 different countries. Our mission is to support students to develop into creative, critical, responsible and
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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strong background in CFD and/or DEM, A strong numerical background with proficient programming skills, Strong motivation, problem-solving skills, and the ability to work both independently and as part of a
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
command of written and spoken English Basic programming skills and basic knowledge in the fields of machine learning and material simulations (i.e., quantum chemistry, density-functional theory, machine