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., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud technologies We are actively involved in practical applications through partnerships with
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Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud
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inverse modeling methods, machine learning, and artificial intelligence techniques. Appointment Details: Start date: As early as February 1, 2026. Annual Salary: $52,000 Application review: Ongoing until
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field. Demonstrated experience with single-cell and/or spatial transcriptomic analysis (Scanpy, Seurat, Squidpy, etc.). Strong programming proficiency in Python and R; experience with machine-learning
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Summary This position will provide technical support to data management plan development, data management, and assist Post-Doctoral Fellows with the development of machine learning methods. Organizational
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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Excellent organizational, communication, and teamwork skills Experience with dynamic causal modelling (DCM), machine learning or related computational approaches are an asset Roles and Responsibilities
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to the role (including OpenSpecimen database and Genemapper software) and capable of quickly learning and utilizing additional computer programs as needed
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first author publications in reputable peer-reviewed journals Advanced quantitative skills (e.g., advanced stats [MLM], machine learning, data mining). Willingness to develop desired skills (see directly
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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum