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researchers and students Explore new funding opportunities Or, in other words, build up your own research field! Your Profile: Master degree and doctoral degree (PhD) in electrical engineering, physics
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Postdoc – Synthesis and up-scaling of high-performance active materials for Na solid-state batteries
electrode active materials, especially for the positive electrode (cathode), still need to be further developed in order to achieve similar performance to current Li-based active materials. Therefore, within
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masters degree and subsequent Ph.D. degree in Computer Science, Mathematics, Physics Engineering or in a similar field. Alternatively an excellent masters degree with professional experience Very good
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Computer Science, Mathematics, Physics Engineering or in a similar field. Alternatively an excellent masters degree with professional experience Very good knowledge and proven skills with larger deep learning
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simulations of CG model enzymes and their constructs to optimize the overall catalytic activity. The work will be done in collaboration with Prof. S. Kondrat from the Institute of Physical Chemistry in Warsaw
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genomic data using deep learning methods in order to identify degrading enzymes from different data resources Using Hidden Markov Models and similar tools as well as machine learning for the identification
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results in reputable scientific journals to share knowledge and contribute to the advancement of the field Your Profile: Master`s degree and PhD in the field of economics, social sciences, data science or a
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the modelling pipeline Your Profile: A university degree (Master) with subsequent PhD in Applied Mathematics, Mathematical Biology, Computational Physics/Engineering or related fields with strong relation
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training on the High Performance Computers, including JUPITER, Europe`s first exascale computer Prepare, process and publish datasets and benchmarks for self-supervised learning in science Engage in national
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respect to the identification and functional annotation of genes involved in, for example, cell wall degradation, carbon flux etc. Screening metagenomic and genomic data using deep learning methods in order