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or human-computer interactions studies. The focus of the PhD-thesis needs to contain knowledge areas such as learning theory, cognitive theories with applications on studies of learning, design of learning
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Assurance and Insurance, Quantum Trust, Privacy-preserving Machine Learning, Privacy-preserving Multi-party Computation, Verifiable Computation, Trustworthy Systems, Adversarial Machine Learning, Assessing
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European
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experiments, machine learning libraries, or reinforcement learning environments; • Good written and oral communication skills; • Ability to work independently and collaboratively in an interdisciplinary
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads
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intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
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; data analysis; modeling; statistics and machine learning; scientific simulation; or theoretical astrophysics. COMPENSATION AND BENEFITS The full-time annual compensation for this position is $95,000. In
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statistical methodology, including genomic prediction, crop simulation and machine learning, to improve prediction of crop yield and related traits. Supervision and Researcher Development: Assist with mentoring
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theoretical statistics, statistical machine learning, high-dimensional inference, empirical process theory, stochastic modeling, optimization, or related areas. • Experience with writing and developing
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combination immunotherapies. Development of NK cell and CAR-NK cell therapies. Building on advances in cellular engineering, we develop and optimize NK cell-based immunotherapies, including chimeric antigen