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mechanical engineering, or related field to apply. A strong publication record is encouraged and previous experience in areas such as Neural network vulnerabilities and defenses, Anomaly detection, Adversarial
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their effective start date. This position is for a post-PhD trainee preparing for a research career path in academia or industry. The planned position will provide a transition to career independence through
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machine learning, interact with an international network of collaborators, and gain post-doctoral research experience. The ideal candidate is self-motivated and can work independently, has a passion for AI
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on the candidate’s experience and qualification. Candidates should have a PhD in Engineering, Cognitive Psychology, or a related field. Additional Qualifications include: Required Record of peer-reviewed publications
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concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical