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. Programming, coding, and experimental hardware skills (desirable). Strong analytical and mathematical capabilities. A passion for research and a willingness to learn. Excellent presentation, communication, and
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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As a PhD candidate, you will investigate how stress, sleep, recovery and physiological responses influence staff behaviour and the escalation or de-escalation of aggression in residential care
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
for a PhD student to join a project at the interface of biomolecular dynamics and modern data science (ERBIOM project). Our group has a long-standing track record in molecular modeling, molecular dynamics
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Would you like to use cutting-edge artificial intelligence to solve real-world physics and engineering problems that matter? This fully funded PhD studentship offers an exceptional opportunity to do
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learn new techniques and work across disciplines is essential, as is a focus on mechanistic understanding, reaction kinetics, and analytical methods. Candidates should have very good English communication
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science » Information management Economics » Marketing Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 9 Sep 2026 - 23:59 (Europe/Sofia) Country Bulgaria Type of Contract
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characteristics To complete a doctoral degree (PhD), the candidate is expected to: demonstrate strong motivation, curiosity, and a learning-oriented mindset work independently, take initiative, and maintain good
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of expertise Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think and learn than what you currently know. PhD or other research
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be