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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Contribute your computer vision
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territories. The pedigrees reconstructed in each populations are sufficient to estimate some simple quantitative genetic parameters, but they are incomplete and contain errors, which greatly limits
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with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation Implementing machine learning approaches that preserve physical constraints while handling
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for nutrients, light, temperature, the influence of zooplankton or more generally higher trophic levels, as well as other parameters such as parasitism and allelopathy, if possible. The model can build on
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machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
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1: Extension of the coverage and performance of the HLA-Epicheck model through the addition of new antigens. This also includes optimizing the values of certain model parameters. Task 2: Evaluation
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https://www.ubjobs.buffalo.edu/postings/59721 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting Detail Information Position Summary
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determination of inversion parameters. 2. Vp and Vp/Vs tomographic inversion, analysis and interpretation of results (Vp/Vs in relation to Vp and seismicity). 3. Participation in events (workshops, conferences
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with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation Implementing machine learning approaches that preserve physical constraints while handling
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. Optimize the acquisition parameters of 3D-Electron Ptychography (combining ptychography and a limited number of view directions, ie., tomography) and improve or further develop the reconstruction algorithm