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have a PhD or equivalent in a relevant discipline. Experience and knowledge in the field of biofilm formation is essential. Experience with with Galleria mellonella and advanced microscopy methods is
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practice (e.g., Python/MATLAB/C++ and/or established modelling platforms). Familiarity with asymptotic and multiscale mathematical analysis methods to ground proof numerical simulations Strong communication
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into laboratory work to develop RPLD methods to create these novel optically active sapphire elements. You’ll have a solid grounding in physical sciences with an eagerness to understand and solve key challenges. In
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skills and ability to manage and analyse experimental datasets. Ability to work collaboratively across disciplines and communicate methods and findings clearly. Desirable Experience measuring root traits
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–biomolecule or catalytic system simulations Quantum mechanical methods (e.g., DFT or QM/MM) Enhanced sampling or free-energy calculations Programming or scripting for computational research (e.g., Python
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disability and political parties across four cases: Denmark, Germany, Spain and the UK. The role will require using qualitative and mixed methods, for instance; interviews, focus groups, and ethnographic
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the field of biofilm formation is essential. Experience with with Galleria mellonella and advanced microscopy methods is also highly desirable. They should be enthusiastic, well motivated and be able to work
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Science (ECS) (http://ecs.soton.ac.uk ). Ranked in the top 1% of universities globally and among the UK's top 20 for research, the University of Southampton has an international reputation for its research
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software framework for the testing of age estimation technologies (AET) from facial images This is an exciting opportunity to contribute to cutting-edge biometric research at the intersection
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candidates who are working towards or nearing completion of a relevant PhD qualification. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/409874/research-fellow-in-… Requirements