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deadline: 16 October 2026 Apply now Do you want to develop a foundation model for one of biology’s most complex ecosystems? By joining the European Innovation Council (EIC) Pathfinder project NOAH, you will
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, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across
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: Develop physics-based, data-driven, and hybrid (physics-informed ML) models of thermal systems to capture dynamic thermal behavior Validate models against experimental data and refine model accuracy and
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, research, startup, or product development environments. Experience integrating analytics, AI, machine learning, or data-driven features into applications. Active GitHub portfolio or examples of deployed
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language models (LLMs) and vision-language models (VLMs), you will investigate AI behavior, develop innovative evaluation methods, and translate scientific insights into real-world applications that improve
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, physician compensation, and hospital partners to develop data driven recruitment strategies, business plans, financial analyses, and market assessments that align with organizational priorities. Job Duties
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Classification Title Postdoctoral Researcher Working Title Postdoctoral Research Scientist Brief Position Overview We are seeking a postdoctoral researcher to join a newly funded DOE project, developing AI-driven
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LiDAR based foundation models to radar, as well as the development of multimodal foundation models incorporating radar. A further challenge is how different radar representations and sensor configurations
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/data-driven modelling; parameter identification and optimization; scientific software development. Importantly, direct experience with PVD is not mandatory. Candidates with strong backgrounds in
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approaches include data-driven parameter estimation for white-box models, the development of black-box models using machine learning methods (e.g., neural networks) and their combination (grey-box). The thesis