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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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Glide, AutoDOCK) Experience with molecular dynamics simulation packages (AMBER, NAMD, GROMACS) Familiarity with high-performance computing or GPU-accelerated simulations Interest in G protein-coupled
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science. Your main responsibilities will include: Characterization of biologics (antibodies, proteins, siRNA) in the presence of excipients using SAXS and complementary biophysical techniques Development
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to identify mutations and small-molecule inhibitors capable of disrupting BAF-centered protein-protein interactions • apply molecular docking (Glide, AutoDOCK) and molecular dynamics simulations (AMBER, NAMD
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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of the project “PROSPER: Predictive models for sustainable protein recovery”, funded by FEDER and by National Funds through FCT (Operation No. 15391 — COMPETE2030-FEDER-00907300), under the following conditions
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qualifications: Experience with implementation or applications of large machine learning models Experience with generative methods for protein design and/or docking simulations or generative methods
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provide documentation from their supervisor confirming that the defense will be completed before the start of the position. Experience in at least two of the following areas: directed evolution, protein