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methods will be advantageous: Microbiological techniques, as well as computer-based analysis Molecular biology techniques Analysis of high-throughput datasets (DNA seq, microbiological data, competitive
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, stable homotopy theory, computer algebra. All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based
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simulations, including AI-based methods. The project associated with this position aims to take advantage of a virtual library of more than 1 million organometallic bifunctional catalysts, optimised
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Strong background in data management and computation Strong background in computer programming Strong background in relevant mathematical modelling Experience with interdisciplinary work A keen interest in
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large datasets analyses Active participation in LALP Lab activities Required selection criteria You must have completed a doctoral degree in cognitive science or computer design/programming Training and
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. Broad interests including some of the following: Higher category theory, stable homotopy theory, computer algebra. All candidates and projects will have to undergo a check versus national export
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-history theory Strong background in data management and computation Strong background in computer programming Strong background in relevant mathematical modelling Experience with interdisciplinary work A
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qualifications: A strong background in algebraic topology. Experience in any of the following: Higher category theory, stable homotopy theory, simplicial methods. An interest in computer algebra and programming
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knowledge within advanced modelling/analysis methodology Applicants must have hands-on experience working with model lipid membranes Applicants must be proficient with computer programing Fluent oral and
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educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab