Research Associate in Computational Methods for Structural Biology
University of York Department of Chemistry
United Kingdom

Research Associate in Computational Methods for Structural Biology

Based at:University of York - Heslington Campus
Hours of work:Full-time
Contract status:Fixed term
Salary:32,817 - 40,322 a year
Posted Date:22/06/2020
Apply by:23/07/2020
Job Reference:8652

Role Description


The York Structural Biology laboratory within the Department of Chemistry wish to recruit a Research Associate in Computational Methods for Structural Biology to work on the BBSRC-funded project “CCP4 Advanced integrated approaches to macromolecular structure determination”, which is a large collaborative project as part of the UK CCP4 consortium and spanning five institutions. Funding is available for a fulltime post (with flexibility if required) for up to 42 months in the group of Professor Kevin Cowtan.

The Department of Chemistry is one of the largest and most successful academic departments at York, as a Department we strive to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel. We are proud of our Athena SWAN Gold Award.


You will conduct research projects under the supervision of senior colleagues, specifically to:

  • Further develop and optimize methods for the refinement of atomic models without the use of atomic parameterizations
  • Develop fragment rebuilding methods based on known protein structures for local rebuilding of model features
  • Develop a fast method for preliminary regularization of protein geometry
  • Incorporate these developments in a user-friendly software tool and document the project in a form which enables reuse by others

Where appropriate you will:

  • assist in the identification and development of potential areas of research and the development of research proposals
  • provide guidance to other staff and students, as required, as well as coordinating the work of small research teams
  • write up research results and disseminate them through publications, seminar and conference presentations and public engagement and outreach activities.
  • assist with undergraduate teaching in own area of expertise

Skills, Experience & Qualification needed

  • A first degree in a science, mathematics or computing field, and a PhD in a chemical/biological science with a strong computational component
  • Knowledge and competency in computational science and a range of research techniques and methodologies, including computer programming in a modern object-orientated language, software development, computation methods and tools, and machine learning.
  • Knowledge of structural biology data and methods
  • Skilled in the use of crystallographic data formats and sources
  • Experience of C++ programming.
  • Highly developed oral and written communication skills
  • Highly developed oral and written communication skills
  • Ability to write-up research work for publications and to present to conferences
  • Ability and experience to develop research objectives and carry out individual and collaborative projects, planning and prioritising own work in order to meet deadlines
  • Highly motivated and professional and collaborative work ethic, committed to high quality research and a willingness to proactively support colleagues and students
  • Ability to work within a team environment and to work independently using own initiative and with attention to detail

Interview date: to be confirmed

For informal enquiries: please contact Professor Kevin Cowtan on

The Department of Chemistry values all employees for the qualities and skills they bring to the workplace and aims to be a diverse and egalitarian community in which all can thrive

The University is committed to promoting a diverse and inclusive community  – a place where we can all be ourselves and succeed on merit. We offer a range of family friendly, inclusive employment policies, flexible working arrangements, staff engagement forums, campus facilities and services to support staff from different backgrounds.

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