Department of Biochemistry University of Oxford Department of Biochemistry
University of Oxford
South Parks Road
Oxford OX1 3QU

Tel: +44 (0)1865 613200
Fax: +44 (0)1865 613201
Image showing the global movement of lipids in a model planar membrane
Matthieu Chavent, Sansom lab
Anaphase bridges in fission yeast cells
Whitby lab
Lactose permease represented using bending cylinders in Bendix software
Caroline Dahl, Sansom lab
Epithelial cells in C. elegans showing a seam cell that failed to undergo cytokinesis
Serena Ding, Woollard lab
Collage of Drosophila third instar larva optic lobe
Lu Yang, Davis lab
First year Biochemistry students at a practical class
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Postgraduate Research Studentships

Department of Biochemistry Studentships

In collaboration with the Medical Sciences Division and Colleges, the Department awards a number of Postgraduate Research Studentships each year. These are full awards that will cover University and College Fees and funding for living expenses. All applicants that apply by the early January deadline will automatically be considered for one of these awards.

 


Group Leader and Project-specific Studentships

In addition to Department of Biochemistry Studentships, we occassionally advertise studentships that are associated with a specific Group Leader or Project. Details about these studentships are given below.

There is a Group Leader/Project-specific Studentship currently available in the Department:


4-Year PhD Studentship: Machine Learning with Molecular Dynamics to improve rapid protein-ligand predictions.

Main academic supervisor: Phillip Biggin

Project description:

Exciting progress has been made in ensemble-based, thermodynamically rigorous approaches to calculate the free energy of binding of small molecules to proteins and indeed recent work by us and others has demonstrated that these methods are capable of obtaining accuracy comparable to experiment. However, these approaches require large amounts of computer time and whilst that may be acceptable in some scenarios it prohibits the use of these approaches in scenarios where real time data is necessary (such as structural refinement or virtual screening). Thus, it would be desirable to develop approaches that are rapid, yet can deliver at the required level of accuracy. Deep learning and related machine learning technologies show great promise in this area, particularly where large data sets are available. Molecular dynamic (MD) simulations can provide huge amount of relevant data about protein-ligand interactions, but thus far these two disciplines have not really been combined. Our overarching question is: "Can machine-learning be combined with MD to improve rapid protein-ligand predictions?"

One of the key advantages of machine learning methodologies, as well as their speed, is their capacity to explain non-linear relationships, which is especially useful in the context of interactions between a protein and a ligand. The work we are proposing here will use MD data within a machine-learning context (neural networks in the first instance, and then deep neural networks) to improve affinity and pose predictions of small molecule binding to proteins. This is an exciting opportunity to improve the prospects for rational drug design.

Further information and background reading: This project is supported through the Oxford Interdisciplinary Bioscience Doctoral Training Partnership (DTP) studentship programme. The student recruited to this project will join a cohort of students enrolled in the DTP's interdisciplinary training programme, and will be able to take full advantage of the training and networking opportunities available through the DTP. For further details please visit www.biodtp.ox.ac.uk

Attributes of suitable applicants: Some programming experience would be helpful but not essential. A good knowledge of (bio)chemistry is however essential.

Funding notes: This project is fully funded for four years by the Biotechnology and Biological Sciences Research Council BBSRC for UK/EU students. Successful students will receive a stipend of no less than the standard RCUK stipend rate, currently set at £14,777 per year which will be supplemented by a further £2500 from the industrial partner.

Application deadline: 13th July 2018. Application to be done at www.ox.ac.uk/admissions/graduate.courses/course-open-for-studentships?wwsl=1


 

College Scholarships

College Scholarships include:

E.P. Abraham Scholarship in the Chemical, Biological/Life and Medical Sciences at St Cross College

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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