Sort by
Refine Your Search
-
structural methods, designing experiments, testing hypotheses, and analysing multidimensional datasets across crystallography, cryo-EM/cryoET, and biophysical assays. You will contribute to publications
-
of the resulting materials will be undertaken using thermal, mechanical and rheological methods, as well as using spectroscopy and GPC methods. Materials will be tested in applications and end-life recycling
-
(or be near completion), with established expertise in Computational Mechanics, Constitutive Modelling, and the Finite Element Method. Informal enquiries may be addressed to Prof. Laurence Brassart
-
methods (Uphoff PNAS 2013; Robb, Sci Reports 2019; Zagajewski, Nature Comm Biol 2023, Chatzimichail, Lab-on-a-chip 2024) and applying them to proteins functioning on DNA and RNA (Stracy, PNAS 2015; Mazumder
-
with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
-
) prior to taking up the appointment. The research requires experience in biological mass spectrometry methods, including HDX MS, and substantial molecular and cell biology experience. You will be expected
-
scientists, forming small teams focused on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor
-
access, analytical methods, and protocols, maintain clear documentation, and coordinate data exchange with partner sites and repositories. They will contribute to project design, manuscripts, presentations
-
to be analysed together with their bound lipids, small molecules, and post-translational modifications. These methods provide mechanistic insight directly relevant to drug discovery. The successful
-
. Experience in the expression and purification of recombinant proteins as well as biochemical and biophysical characterisation methods are essential. You will possess sufficient knowledge and experience in