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, with particular emphasis on atherosclerosis. The project builds on and complements the institute’s expertise, led by Prof. Oliver Soehnlein, in understanding how neutrophils drive chronic sterile
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of transportation and energy. Its experimental and numerical modeling activities focus on various complex and multiphysical flows, including turbulence, two-phase flows, combustion, and thermoacoustics. Research
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understand, explain and advance society and environment we live in. Your role Conduct research and prepare a doctoral thesis in metabolic network modelling and computational epigenomics Develop novel methods
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Matthew Jones, Prof R Lewis, Prof D Fletcher, Prof David Curtis Application Deadline: 07 November 2025 Details Are you enthusiastic about digital technology and motivated to build tangible change
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 23 days ago
Doctoral Candidate in computational neuroscience. (m/f/d) The position The position is part of an international collaborative effort (4 labs) to test computational models of episodic and spatial memory by
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biodiversity recovery and climate mitigation and adaptation. The post holder will work closely with Prof. Andrew Friend and the wider CLR team. They will also have the opportunity to participate in a wide range
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wound healing. Under the supervision of Asst. Prof. Konstantinos Kalogeropoulos and Assoc. Prof. Erwin Schoof, the PhD candidate will join the Protease Systems Biology group embedded in the Cell Diversity
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). e) Experience in musculoskeletal modeling and finite element modeling (preferred). Academic degrees obtained in foreign countries shall be registered by a Portuguese institution, according to
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program at a Portuguese higher education institution - At least one publication in preparation on conceptual modeling applied to the socio-ecological system related to soil management in the Montado system
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design automation tools for analog, RF and millimeter-wavelength IC design. It focuses on the automation of analog circuit design utilizing diffusion models and/or other state-of-the-art generative