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; • Experience in data analysis and visualization. Minimum requirements: • Experience in Python; • Knowledge of optimization algorithms; • Knowledge of modelling or simulation. 5. EVALUATION OF APPLICATIONS AND
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health data visualization tools, including the HeatRisk Tool and Heat and Health Tracker, under mentor guidance. Participate in collaborative discussions with CDC scientists and partners to gain insight
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of Computer Science at UNNC is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and
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, Evaluation methods, Mixed methods research, GIS/spatial analysis, Community and/or transportation planning, and Data visualization. Point of Contact Rachel Eligibility Requirements Citizenship: U.S. Citizen
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Details Title Postdoctoral Fellow School Faculty of Arts and Sciences Department/Area Molecular and Cellular Biology/Applied Physics/SEAS Position Description Our lab is developing a series of
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programming and academic initiatives, the IMC advances critical engagement with visual culture and supports interdisciplinary scholarship in photography and lens-based practices. The IMC is also home to
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 3 months ago
, structural biology, computational biology or a related field, and experience in computational structural biology, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization
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30 Jul 2026 Job Information Organisation/Company INESC TEC Research Field Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1) Application Deadline 13 Aug 2026 - 23:59
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Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing, transport, healthcare and others. Your Remuneration
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, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization, and interdisciplinary work at the interface of proteomics, structures and machine learning. Track 2