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, or relevant fields. Excellent programming skills in modern programming languages are required, as well as experience in computational or mathematical modelling. Experience with the analysis of biological data
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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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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-resolved microscopy data Collaborate with other computational researchers to build better models Collaborate with experimental researchers to validate predictions Present findings at scientific meetings and
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space Collaborate with other computational researchers to build better models Work closely with experimental researchers to guide synthesis and validate computational predictions Present findings
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design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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molecules and solids. This work involves data-driven analysis of electronic structure calculations to reduce computational time. The modeling of large systems will also include development of specialised
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materials for synthesizing different types of hydrogen storage molecules. Using advanced quantum mechanical calculations, you will develop multi-scale models to study reaction kinetics and improve catalyst
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of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department