I studied Physics Engineering at Politecnico di Milano (Milano, Italy), where I earned a bachelor’s degree followed by a master’s degree. Both of them consisted mainly of solid state physics classes, with a particular focus on semiconductors (for electronics and photonics application) and magnetic nanostructures. My first experience in research was at the European Synchrotron Radiation Facility (Grenoble, France), where I spent 10 months working as a trainee for my master thesis project.
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Brief description of project:
Transmembrane proteins (TMPs) bring particular challenges to the structural biologist throughout structure determination. This project leverages recent advances in TMP multi-crystal data collection using micron sized X-ray beams and in structural bioinformatics methods, aiming to increase the efficiency of TMP structure determination.
At Liverpool, the student will work at the interface between structural bioinformatics and experimental structural biology, devising software solutions to help solve more TMP targets by Molecular Replacement (MR). These solutions will exploit the recent availability of evolutionary covariance-based predictions of contacting residue pairs. This additional information, readily obtained for targets in medium to large protein families, will drive three routes of unconventional MR. First, TMP-specific contact predictors will be used to build better ab initio models. Secondly, an innovative fragment-based approach to MR will be explored, using contact predictions to select promising structural fragments, containing multiple secondary structure elements, to act as MR search models. Thirdly, emerging software to align (predicted) contact maps will be use to match (regions of) targets to (regions of) PDB entries, identifying structural units, distantly related or unrelated, that may serve as search models.
At Diamond, the student will explore effective methods for the measurement and analysis of TMP diffraction data will be explored using both X-ray and electron diffraction approaches. This will encompass TMP crystal sample preparation, data collection and analysis. The student will devise and characterise novel metrics of data quality and distribution and test their relationship to solvability using the novel MR methods developed in Liverpool. The results will also feed into ongoing machine learning-based efforts to predict target tractability from characteristics of the crystal itself and data it yields.
The training element of the project is strong, from software development through to use of cutting edge infrastructure at Diamond - the VMXm beamline and Electron Diffraction facilities.
Applications to this studentship are now open. APPLY NOW
Application deadline: Friday, April 06 2018.
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