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computational and data‑analysis methods and software, including simulation, modelling, and data management. To strengthen the field of computational science at the Faculty of Science, we are now advertising two
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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-Doctoral Associate (PDA) to engage in cutting-edge research on channel modeling and characterization for communication and sensing in emerging spectrum for 6G and beyond, with a focus on the FR3, THz and
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related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core job duties include
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for high-dimensional datasets, including spatial bulk and single-cell RNA sequencing, mass and flow cytometry, and imaging data derived from both patient samples and experimental models. The overarching aim
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and mitochondrial biology: primary human fibroblasts, mitochondrial bioenergetics, import assays, respiratory chain phenotyping, in vivo disease models. Multi‑omics: single‑cell and bulk transcriptomics
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loadings. It combines experimental data, finite element simulations, and probabilistic models. Results depicted on Fig. 1 and Fig. 2 show high extrapolation and interpolation capabilities of the obtained
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discussion sessions; participate in simulation and physical diagnosis and skills labs Develop criteria and procedures for didactic and/or clinical courses consistent with ARC-PA Standards Perform additional
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Postdoctoral Fellow in Neutrino Astrophysics Position in the School of Physics - Otte Research Group
simulations, neutrino physics, statistical inference, detector modeling, or large-scale computing frameworks is highly desirable. Applicants should submit the following: • Cover letter • Statement of research
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the following is desired: - Agentic and sequential decision-making for autonomous experimentation, including active learning and optimal experimental design - Generative and probabilistic modeling