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Python) and data analysis or machine learning applied to materials science Ability to work in interdisciplinary project or industrial experience About the employment The employment is a temporary position
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. Previous experience with machine learning applications in molecular modelling, including experience with at least three of the following Python libraries: TensorFlow, PyTorch, JAX, RDKit. Previous
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methods, including GIS and spatial analysis. Applicants are invited to visit our departmental website to review the kinds of research we do in the department (https://www.uu.se/en/department/human-geography
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on developing biochar as a sustainable feedstock for hard carbon anodes in sodium-ion batteries. In collaboration with Besca AB (https://www.bescacarbon.com/ ), this project explores microwave plasma technology
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through
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: Analyze spectroscopic and kinetic data, employ statistical and machine learning approaches where relevant, and contribute to manuscripts, presentations, and reports. Collaboration: Work closely with project
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(especially neuromorphic) device, circuit and system design, clean-room fabrication, ferroelectric (or antiferroelectric) materials and devices, memristors, tactile sensors, FPGA/MCU/API development, machine
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department's activities is available at https://www.uu.se/en/department/medical-sciences Project Description This doctoral position is part of HEPARD (Health Economic Policy Advice with Real-World Data), a Marie
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to develop within and acquire the doctoral education. Additional qualifications We are looking for a highly driven person, who shows clear signs to perform research work independently and can work effectively