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-scale GAC filter data to aid in system understanding, design, and optimisation. Main responsibilities Conduct research within the PhD project (>80%) Publish scientific articles and present your work
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and determination? We are currently seeking a/an PhD in AI-assisted proteomic data analysis applied to Human Health 50 Faculty of Life Sciences Job vacancy starting: 01.09.2025 (MM-DD-YYYY) | Working
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function Data analysis. Main responsibilities Conduct research within the PhD project (>80%) Publish scientific articles and present at conferences Contribute to departmental teaching or other duties (<20
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Reliable AI-powered Data Analysis in collaboration with the University of Amsterdam. Interested
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effective strategies for preventing, identifying and stopping the abuse of older people? While the advanced methods training of the PhD will be data science and statistical analysis, there will also be
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using a range of geoelectrical techniques, GHG soil flux measurements and associated soil-based analyses, as well as analysis of ecosystem GHG fluxes and remotely sensed data. We will support the PhD
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; Monash University, Australia | North Adelaide Melbourne St, South Australia | Australia | about 14 hours ago
Centre for Health Economics, Monash University Centre for Health Economics, Monash Business School, Integrated PhD Program 2026 Location: Caulfield campus, Monash University, Melbourne, Australia
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approaches, including principal component analysis and machine learning, to handle multivariate datasets. Prior experience in data science is not essential; the successful candidate will be supported through
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, you will: Design and perform fluorogenic and nano-photonic DyeCycling experiments. Write/adapt analysis code to process fluorescence trajectories and extract kinetic information. Evaluate bioconjugation
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust