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- University of Warsaw: Faculty of Mathematics, Informatics and Mechanics
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
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: access to professional development, social benefits, and training opportunities. More information: https://en.bsp.uw.edu.pl/researchers/ Basic responsibilities and obligations The selected candidate will
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a competition for the position of postdoctoral position (assistant professor) in the NCN Sonata-18 project entitled: Parallel and exact algorithms for path problems in directed graphs. About the
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Mechanics, University of Warsaw, Banacha 2, 02-097 Warsaw. Employee benefits: access to professional development, social benefits, and training opportunities. More information: https://en.bsp.uw.edu.pl
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breakable with advances in computer algorithms. Quantum technologies offer solutions to such problems, enabling processes that are impossible with standard methods. However, even though few examples
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preparing libraries for next-generation sequencing (NGS) as well as nanopore sequencing, along with the ability to analyze sequencing data using bioinformatics algorithms. Proficiency in developing algorithms
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, University of Warsaw, Banacha 2, 02-097 Warsaw. Employee benefits: access to professional development, social benefits, and training opportunities. More information: https://en.bsp.uw.edu.pl/researchers/ Basic
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working conditions Place of work: Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, 02-097 Warsaw. Employee benefits: access to professional development, social benefits
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Offer Description The successful candidate will be expected to work primarily on aspects related to precision predictions for the LHC and parton-shower simulations. The project encompasses the development
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dimensionality reduction * development of optimization algorithms and numerical modeling procedures * development of simulation models using commercial packages (CST, ADS, HFSS, etc.) * writing technical reports
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identifying the parameters of PDEs, while on the other, newly emerging gradient flow methods hold significant potential for the development of sampling algorithms. The research goals are structured