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interested in digital mental health research. We are looking for individuals with a strong commitment to data-driven digital assessment, monitoring, and treatment of serious mental illness. Individuals with
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Core Leadership Team and individual Study Leadership Teams. The first ManyBirds study, recently published (ManyBirds Project et al., 2025), provided the first large-scale comparative data on neophobia
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vision transformer or large vision AI model Expertise in high performance computing Expertise in image and spatiotemporal data processing Expertise in federated learning on large computing clusters A
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, statistics, computer science, physics, etc. Prepares and edits research papers, proposal, and reports. Performs advanced testing procedures and analyses of data. May prepare samples for testing. Performs
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At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 13 hours ago
on an NSF-funded project involving geospatial modeling, AI/GeoAI methods, and spatial data integration. · Design, implement, and evaluate deep learning and/or generative AI models using large-scale geospatial
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on emergency medicine health services, care transitions, and population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR
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, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several
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. The research focus will be on developing and applying first-principles-based and data-driven computational methods to understand multiscale processes and to accelerate chemical discoveries for renewable energy
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. Automated data-driven selection procedures will enable to gain objectivity and capacity to handle large amount of data from a wide range of epidemics. The first challenge consist in refining previous models