917 evolution-"https:"-"https:"-"https:"-"https:"-"UNIVERSITY-OF-HELSINKI" PhD positions
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) Experience in dependable systems, real-time and embedded systems and/or operating systems and the threats and attacks they are exposed to is highly valuable, systems development experience is an asset Hard
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inclusive learning and working environment that honors the talents, respects the differences, and nurtures the growth and development of all. We seek to attract faculty and staff who share our commitment
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
life. It also provides valuable skills in AI, materials testing, and data analysis. In addition to its technical innovation, this project offers a range of unique personal and professional development
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interest in regenerative medicine and the development of cell therapies. Meritorious for the position are: Previous experience with projects focusing on neurodegenerative diseases Experience or training in
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foundation, strong learning and research abilities, communication skills, excellent academic performance, outstanding work achievements, and strong potential for development Be under 35 years old (at 1st
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development, collaborate with experts across disciplines, and contribute to open-source tools that advance the wider AI community, and support long-term societal impact. We welcome applicants from background
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meet the agreed requirements, you will then progress to the PhD project component, which involves high quality research training and career development, culminating in a written thesis on the topic
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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Description of the offer : In the development of sustainable materials and manufacturing, residual stress forces hidden within a material can cause serious problems, compromising performance and
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how individuals make movement and life-history decisions in dynamic agricultural landscapes. A baseline model and dynamic energy budget framework already exist, but require development to incorporate