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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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techniques may be employed to support the modeling of uncertainty, along with the formulation and resolution of planning problems using stochastic optimization methods. Key Responsibilities The selected
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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(preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models to the clinic The post holder will be based in the Department
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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in applied mathematics, field methodologies in unconsolidated sediments and/or numerical modeling is preferred. Candidates should have a publication record in hydrogeology and/or related fields
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Job posting (PHY 06/2025) The Leibniz Institute for Baltic Sea Research Warnemünde (IOW) has a temporary vacancy starting 01.01.2026 for a Postdoctoral position in regional ocean climate modeling in
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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will design climate change mitigation scenarios that respect both climate targets and sustainable development goals using the REMIND model, one of the world’s leading integrated energy-economy-climate