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will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity
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recognitions and multi-class neural network algorithms. We propose to apply this emerging method to study samples from Europe, South Africa, and East Asia dated between 1.8 Ma and 60 thousand years ago (ka
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and
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, we are looking for candidates to have the following skills and experience: Essential criteria PhD in neuroscience, psychology, psychiatry, biomedical engineering, or related discipline. Documented
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, we are looking for candidates to have the following skills and experience: Essential criteria PhD in neuroscience, psychology, psychiatry, biomedical engineering, or related discipline. Documented
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to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and
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the research topics that excite us as a group include: (i) Ethics of AI and Automation; (ii) Social Media Analysis (iii) Algorithmic Privacy, (iv) Analysis of Academic Collaborations, (v) Human-Bot
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space)? What are appropriate descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms
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computers or atomic-physics platforms, and quantum algorithms for quantum many-body physics. A PhD in Physics is required. The ideal candidate will have numerical simulation skills with exact diagonalization