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Field
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Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and Homomorphic Encryption. (3) AI for Science: Applications of Artificial
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans for patients with chronic diseases. Analyzes complex sensor data, works with a
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fixed-term position, eligible for renewal based on grant funding. Northeastern University's Institute for Experiential AI has established a position for a ML Performance Engineer, Computational Biology
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algorithms and software for data analysis. Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communication
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(PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must
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/change data input, files/database structures, data transformation, algorithms, and data output by using appropriate computer language/tools to provide technical solutions for complex application
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scientists cross-trained in molecular and computational approaches. We seek to create a positive, high-energy environment with open and honest communication to empower individuals to discover and refine
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to: Quantum Computing Theory Quantum Algorithms Quantum Networking for Distributed Quantum Computing (As opposed to QKD) Quantum Machine Learning Quantum Sensing Quantum Applications Quantum-safe or Quantum
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and expressing the mathematical properties of existing algorithms in preparation for publication and peer review. The algorithms are written, tested, and functioning. Timeline is ~3 months. Compensation
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and