(Senior) Data Scientist

Updated: about 1 month ago
Location: Didcot, ENGLAND
Deadline: 31 Jan 2021

Full Time/Part Time

Fixed Term (2 Years)

This post is one of the four interleaved positions connecting the Alan Turing Institute, The Science and Technology Facilities Council (STFC), University College London (UCL), Medical Research Council, Laboratory of Molecular Biology (MRC-LMB) and the University of Cambridge.

This position will incorporate the Scientific Machine Learning (SciML) and CCP-EM (Collaborative Computational Project for Electron cryo-Microscopy) which are co-located at the Rutherford Appleton Laboratory (RAL) in Oxfordshire, alongside the Electron Bio-Imaging Centre (eBIC).

The Harwell campus is home to the Rutherford Appleton Laboratory (RAL) and to the UK research community’s large-scale experimental Facilities. These include the Diamond Synchrotron and Electron Microscopy facilities, the ISIS Neutron and Muon Facility, the Central Laser Facility, and Centre for Environmental Data Analysis (CEDA). Researchers from universities and from industry use these facilities for a very wide range of scientific applications ranging from revealing ancient fossils and improving battery technology, to characterising materials to understanding the impact of climate change.

About the role

Within this post, you will leverage the skills and experience in the SciML and CCP-EM groups to produce a rich metadata pipeline which will allow datasets to be achieved effectively to provide rich training data. This will empower the development of next-generation ML algorithms for this project, through the collaborations at the partner sites, as well as for other developers in the cryoEM community. Furthermore, you will use the metadata collected to learn optimal processing pathways to guide new users and improve automated pipelines. You will also explore how the dynamic reconstructions can be applied to atomic models using steered molecular dynamics.

Responsibilities include:

  • Develop ML or relevant techniques to understand, interpret and extract features from experimental datasets
  • Implement these techniques in a commonly used programming language, like Python
  • Gather annotated datasets that can be used to develop future ML algorithms
  • Contributing to learning and development at the Rutherford Appleton Lab, and supporting its community by:
    • Presenting work internally and externally
    • Publishing work in peer-reviewed journals
    • Helping researchers to understand the power and limitations of Machine Learning technologies applied to their real-world data
    • Assisting in running training courses and providing consultancy to both university and industrial users.

To be successful in the role you will be educated to PhD level D in a relevant scientific or computer science discipline (or will have equivalent experience).

You’ll also be expected to have an awareness of software engineering principles and familiarity with one or more machine learning toolsets (e.g. SciKit Learn, TensorFlow, PyTorch).

You will be able to demonstrate evidence of collaboration during software development or scientific research and of strong scientific communication skills.

As part of UK Research and Innovation, STFC offers a benefits package designed to provide an excellent work/life balance. This includes 30 days’ annual leave, 10.5 public and privilege days, Christmas shut down, flexible working hours, an exceptional defined benefit pension scheme.

Applicants are required to include a cover letter outlining their suitability for this role.

Applications are handled by UK SBS; to apply please click the apply button. Applicants who are unable to apply online should contact us by telephone on +44 (0)1793 867000.

The closing date is 31st January 2021.

View or Apply

Similar Positions