Biography

I am a Research Software Engineer at Lancaster University. I work in the Data Science Institute to support all Researchers at Lancaster University. I will be providing training to all Researchers at the University in reseaech computing and software skills such as:

  • Using the command line
  • Git for version control
  • Introduction to R/Python

I also provide support for the N8 computing cluster “Bede” for researchers at Lancaster.

Previously I worked as a Research Software Engineer at the University of Manchester, working for Research IT. Here I worked on BioExcel as part of Carol Goble’s eScience Lab Group developing and improving software and tools used for computational biomolecular research and analysis workflows.

I am a 2017 Fellow of the Software Sustainability Institute. Through this I have created and taught several course on various skills and software for research, and hosted Research forums for researchers frmo all disciplins to come together and exchange ideas and support each other in using software as part of their research.

I previously worked at Lancaster University in the Experimental Particle Physics Group where I maintained and supported the GridPP computing cluster.

Interests

  • Reproducible research
  • Sustainable Software
  • Training Researchers

Education

  • PhD in Particle Physics, 2011

    Lancaster University

  • MPhys in Physics with Astrophysics and Cosmology, 2008

    Lancaster University

Recent Posts

Latest GROMACS Bioconda release

Detailing the latest release of GROMACS in bioconda and the issues we had to work throught o get there.

Patching Conda

Occasionally, there is a need to patch the source code used in Conda. When it is not possible to fix faulty source code directly, you can patch it, by providing a patch file along side the conda build script. This can then modify and patch the source code just before you build the conda package.

Creating hardware optimised Conda Packages

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. GROMACS strongly benefits from hardware optimisation. Conda is a wonderful way of packaging software to make it easily accessible and to support reproducible research. One downside to using Conda is that the code must be compiled for all systems and then packaged - this means it can run on almost any system, but also means that the application is not optimised for the computer it is ran on - for an application like GROMACS optimisation makes a huge difference in the time taken to run an analysis.

Building GROMACS in docker - part 1

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. GROMACS strongly benefits from hardware optimisation. One of the challenges of using GROMACS in a container is to support this hardware optimisation.

Building GROMACS in docker part 2

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. GROMACS strongly benefits from hardware optimisation. One of the challenges of using GROMACS in a container is to support this hardware optimisation.

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