94 structures-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in Norway
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models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex data structures (e.g., spatial models or second-order meta-analytic models
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structural equation modelling Write at least 4 scientific articles as first author Communicate results in various national and international scientific journals and popular science forums Present
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on peptide-membrane interactions, and in particular, towards characterizing and understanding the dynamical and structural effects of various peptides on both simplified and complex membrane systems
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skills for completing the doctoral degree within the timeframe ability to work independently and in a team, be innovative and creative ability to work structured and handle a heavy workload having a good
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creative ability to work structured and handle a heavy workload having a good command of both oral and written English via Unsplash Requirements for competence in English A good proficiency in English is
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for completing the doctoral degree within the timeframe ability to work independently and in a team, be innovative and creative ability to work structured and handle a heavy workload having a good command of both
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understanding how imaginaries, structures, and agency co-evolve across space and time, contributing to uneven geographies of future-making. The qualifying project will be carried out at the University
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the timeframe ability to work independently and in a team, be innovative and creative ability to work structured and handle a heavy workload having a good command of both oral and written English via Unsplash
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clusters and workflow management tools (Snakemake, Nextflow). Strong scientific writing skills. Ability to work in a structured manner while actively contributing to an interdisciplinary team. Familiarity
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structures for generation of virus capsids and therapeutic proteins for gene therapy. The project will involve both physics-based forward modeling of protein structures and reinforcement learning methods