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Join us in designing stable materials for sustainable energy devices with machine-learning-accelerated simulation and modeling. Work assignments The postdoctoral researcher will develop machine
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the course webpage on the Canvas learning platform, delivering lectures and seminars, providing guidance and feedback on assignments, and conducting evaluations and examinations in accordance with
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learning, optimization, mathematical foundations of artificial intelligence, mathematical ecology and mathematical statistics. Qualifications To qualify as a postdoctoral scholarship holder, the postdoctoral
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Engineering, we are seeking a researcher with a strong interest in developing and applying machine‑learning methods for materials design, in particular steel design. The position is part of our growing research
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authority. Learn more about our benefits and what it's like to work and grow at KTH. Trade union representatives Contact information to trade union representatives. To apply for the position Log into KTH's
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dynamics simulations and machine learning methods to study the structure and electrochemistry of disordered materials are also encouraged to apply. The project primarily aims to understand the complex
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an integral part of KTH’s core values as a university and public authority. Learn more about our benefits and what it's like to work and grow at KTH. Trade union representatives Contact information to trade
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benefits. Equality, diversity and equal opportunities are essential to quality and form an integral part of KTH’s core values as a university and public authority. Learn more about our benefits and what it's
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to quality and form an integral part of KTH’s core values as a university and public authority. Learn more about our benefits and what it's like to work and grow at KTH. Trade union representatives Contact
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven