From: jobs at ccl.net (do not send your application there!!!)
To: jobs at ccl.net
Date: Fri Nov 17 07:44:21 2017
Subject: 17.11.17 PhD studentship ''Advancing structure-based drug design with novel binding free-energy calculations methods'', University of Edinburgh, UK
Applications are invited for a PhD studentship in the Michel lab 
(http://www.julienmichel.net) in the area of biomolecular simulations and 
computer-aided drug design. The start date is September 2018. The studentship
will cover all university fees at the UK/EU level, and includes funds for maintenance
at the standard EPSRC rate.
The EaStCHEM school of Chemistry at the University of Edinburgh is 
among the top ranked departments within the EU.

The prediction of protein-ligand binding affinities is a major goal of modern 
computer-aided drug design. Among existing computational techniques, 
alchemical free energy methods are currently receiving considerable interest from 
the industry to support structure-based drug design campaigns. 
However significant obstacles remain before alchemical free energy methods can be 
widely applied to the full breadth of protein-ligand complexes of pharmaceutical 
interest.

This project will focus on considerably enhancing the efficiency and scope of 
alchemical free energy methods for structure-based drug design problems.
 This will be achieved by implementing and validating novel algorithms that 
substantially decrease the computing time needed to identify promising ligands 
among large datasets of putative drug-like molecules. This project will be carried out 
in close collaboration with a leading computational chemistry software company. This
 is an exciting opportunity to develop, validate and apply next-generation 
computer-aided drug design software and methodologies. 
Upon completion of the studentship, the successful applicant will have gained strong 
technical expertise in molecular modelling and learned to work closely with the 
software and pharmaceutical industry sectors.
This will prepare him or her well for a future career in academia or industry.

Applicants with an excellent academic record in a chemistry/biochemistry/physics / 
high performance computing degree are encouraged to apply. 
The ideal candidate will have: strong knowledge in physical chemistry and/or 
biophysical chemistry; relevant research experience; excellent written and oral 
communication skills;  enthusiasm for rational drug design, computational chemistry 
and scientific computing. 
Previous experience in computer programming (Python, C++) is desirable but not 
essential, provided the applicant is keen to develop skills in this area during the 
studentship.

Applications will be considered until an excellent candidate has been identified and 
applicants are advised to apply as early as possible. 

Candidates should be UK resident, with or about to obtain a 2.i or 1st class degree in 
a relevant discipline. 
EU candidates may be considered, provided they demonstrate an outstanding 
academic record (within top 5% of your class) and strong written/spoken English 
language skills. 
Exceptional overseas candidates may be considered, but this studentship only 
covers stipend and tuition fees at the UK/EU level.
To apply, please submit initially by email a CV, covering-letter describing your 
previous research experience, reasons to apply and justifying your eligibility, 
as well as the names and email address of two referees in pdf format to 
Dr. Julien Michel julien.michel[-]ed.ac.uk. 

Informal enquiries are encouraged.

The School of Chemistry holds a Silver Athena SWAN award in recognition of our 
commitment to advance gender equality in higher education. 
The University is a member of the Race Equality Charter and is a Stonewall Scotland 
Diversity Champion, actively promoting LGBT equality. 
The University has a range of initiatives to support a family friendly working 
environment.
See our University Initiatives website for further information. 
University Initiatives website: 
https://www.ed.ac.uk/equality-diversity/help-advice/family-friendly
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