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Field
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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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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
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working under the supervision of Prof. Jaideep Vaidya (the PI and Director, I-DSLA) to develop and analyze privacy-preserving solutions for biomedical data research, implementing the developed algorithms
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requirements and such other tasks that are assigned to you. Responsibilities: Support PhD students on their research methodologies, experimental designs, and theoretical approach. Participate actively in
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, and improve prediction accuracy - develop Machine Learning and AI algorithms for crop management, yield predictions and decision support systems - prepare manuscripts for peer-reviewed publications
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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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results; support data releases. Qualifications: - PhD in EE/Physics/Optics or related field. - Demonstrated, hands-on experience on DAS, φ-OTDR/OFDR, or other distributed sensing techniques, from design to
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travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding