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statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging, and clinical covariates. Apply
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visualization of high-dimensional omics data from the field of bioeconomics, and in the modeling, simulation, and engineering of biomolecular systems, including enzymes. Apply your data science skills to real
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Aarhus BSS Graduate School, Aarhus University invites applicants for two three-year PhD scholarships within the research project “Decoding Danish Firm Innovativeness from the Consumer Perspective
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of geoinformation systems, cartographic production systems, image data processing and analysis, spatial modeling and animation, geoinformation database technology development and design of geoinformation
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epilepsies. They use a range of advanced genomic techniques including single-cell and spatial multiomic evaluation of epilepsy surgical tissue as well as iPSC-derived neural cultures and mouse models
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Apr 2026 - 00:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date
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individuals who have or will soon receive a PhD in Economics focusing on firm dynamics, structural transformation, economic growth, spatial economics. The appointment is for 3 years and will begin September 1
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
at both national and international levels, as well as the assessment of their application in spatial solutions, with a special focus on wood, metal, and fiber-based technologies; Design of prototype spatial
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guided by supervisors. Doctoral studies end with a thesis and a doctoral degree. More about being a doctoral student at LTH on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ Subject and
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to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within