STFC
Organisation STFC
Organisation Detail Science and Technology Facilities Council
Reference Number IRC249995
Location Didcot See on Map
Salary £30782 - £48962
Date Posted 26 June 2019
Grade UKRI-Band E
Contract Type Open Ended
Hours Full Time
Closing Date 21 July 2019
Interview Date




Brief Description


Salary: Data Scientist £30,782 - £36,459 or Senior Data Scientist £38,318- £46,576 (dependent on expertise and inclusive of sector based RRA)
Grade: UKRI-D or UKRI-E
Contract Type: Open-Ended
Hours: Full time or Part Time (Minimum 18.5 hours per week)
Closing Date: 21st July 2019

Background

The Harwell campus of the Science and Technologies Facilities Council is home to the Rutherford Appleton Laboratory and to the UK research community’s large-scale experimental Facilities. These are the Diamond Synchrotron and Electron Microscopy facilities, the ISIS neutron and muon accelerator, and the Central Laser Facility. Researchers from universities and from industry use these facilities to attack a very wide range of scientific applications ranging from determining protein structures to the physics of materials.

In the last decade, experiments performed at these facilities have become much more complex and now generate very large volumes of scientific data. Increasingly, researchers need support and assistance in all aspects of data science, from the generation and acquisition of the datasets on-site at the Facilities, the use of advanced data analytics to extract new science from their data, and through to data curation, management and archiving.

The Software Infrastructure Division of the Scientific Computing Department has been set up to support the different Facility user communities - in respect of simulation and modelling, of scientific software engineering and of all aspects of data science. The Scientific Machine Learning (SciML) group of the Division is focused on the practical application of advanced AI and machine learning technologies to the analysis of the ‘Big Scientific Data’ generated at the Facilities.

The SciML Group applies its expertise to real-world data science challenges arising from experiments at the Harwell Facilities. As a data scientist in the SciML group, you will work with the Facilities and their users in applying state of the art AI and Machine Learning methods to translate their data into new science. The SciML Group is also a ‘Turing Hub’ – a component of the Alan Turing Institute’s ‘AI for Science’ initiative. The Group runs the PEARL AI computing service for Turing researchers on two state-of-the-art NVIDIA DGX-2 GPU systems.

Working with real-world problems informs our research directions and the ease-of-use, robustness and transparency of these technologies is a major theme. The work of SciML is complementary to the predominantly industry-focused Data Science group at the Hartree Centre on the Daresbury site. With experience gained from working with AI technologies on large datasets, the group will collaborate with the Hartree Centre in providing training and advice not only to university users but also to companies and government.

The post is based at the STFC Rutherford Appleton Laboratory in Oxfordshire.

Responsibilities

  • to apply state-of-the-art and novel data science and other analytical techniques to problems faced by the users of the Harwell Large-Scale Experimental Facilities
  • understand the problems the users are seeking to address and develop appropriate analytical approaches to solving these problems
  • assist users in collecting and managing their data
  • assist in building automated systems, statistical models and applying machine learning technologies to the analysis of the experimental data
  • contributing to learning and development at the Rutherford Appleton Lab and support its community by presenting work internally and externally
  • helping researchers to understand the nature of real-world data
  • assist in running training courses and providing consultancy to both university and industrial users.

To be appointed a Band E you will also be expected to:

  • to play a leading role in the development and evolution of the SciML group
  • to assist in embedding best practice software engineering processes
  • to work with partners and stakeholders to integrate development with the group
  • to assist in developing the strategy for the SciML team within the department.

Contacts and Communication

  • regular contact with staff internally and externally
  • assist in organising and coordinating technical meetings and relevant project events as appropriate
  • maintain effective engagement with stakeholders (e.g. the facilities staff, members of the university research community, other potential partners from industry and government).

Personal Skills and Attributes

  • strong communication skills (verbal, written, and presentation)
  • able to work effectively under pressure, set priorities and make decisions independently
  • able to work with uncertain requirements to develop a consensus on a plan of action
  • ability to manage complex situations with confidence and with little supervision.

To be appointed a Band E, you will have:

  • strong leadership skills
  • ability to delegate effectively
  • proven negotiation and influencing skills
  • proven organisational ability to manage a workload on a range of activities with competing time demands
  • high level of self-motivation and drive, and capable of motivating others
  • analytical with exceptional problem-solving skills.

You must be available to travel/work in the UK and overseas for meetings and events.


Organization Description


UK Research and Innovation is a new entity that brings together nine partners to create an independent organisation with a strong voice for research and innovation, and a vision to ensure the UK maintains its world-leading position in research and innovation. More information can be found at www.ukri.org.

The Science and Technology Facilities Council is a world-leading multi-disciplinary science organisation, and our goal is to deliver economic, societal, scientific and international benefits to the UK and its people – and more broadly to the world.

Criteria will be assessed through shortlisting (S), at Interview (I) or both (S&I)

Shortlisting Criteria

Essential:

  • educated to degree level or equivalent
  • familiarity with one or more machine learning toolsets (SciKit Learn, TensorFlow, etc.) (S&I)
  • experience managing and organising the parameters and results of computational experiments (S&I)
  • demonstrated ability to assimilate new ideas and turn them into practical, applied techniques and willingness to continue to learn new techniques (S&I)
  • excellent written communication skills as demonstrated by CV and covering letter.

In addition to be appointed the Band E position:

  • a PhD or equivalent professional experience in a field with relevance to data science
  • deep understanding of managing, structuring, and analysing data, including building statistical models and using machine learning technologies. (S&I)

Desirable

  • visualisation technologies for understanding large or complex data (S&I)
  • experience working with high performance computing, GPU and cloud platforms (S&I)
  • experience as a collaborative team member on complex projects. (S&I)

Interview Criteria

Essential:

  • ability to work both as part of a team, and with a high degree of autonomy
  • excellent verbal communication skills including the ability to present complex or technical information clearly
  • good problem solving abilities
  • a high degree of responsibility, commitment and reliability
  • good organisational and project management skills.

In addition to be appointed the Band E position:

  • strong leadership skills with previous experience of/the ability to lead, motivate and develop others.

UKRI supports research in areas that include animal health, agriculture and food security, and bioscience for health which includes research on animals, genetic modification and stem cell research. Whilst you may not have direct involvement in this type of research, you should consider whether this conflicts with your personal values or beliefs.

To enable us to hire the very best people we will conduct a full and comprehensive pre-employment check as an essential part of the recruitment process on all individuals that are offered a position with UKRI. This will include a security check and an extreme organisations affiliation check.

Employee Benefits

UK Research and Innovation recognises and values employees as individuals and aim to provide a pay and rewards package that motivates staff to perform to the best of their ability. The reward package includes a flexible working scheme, a Career Average Revalued Earnings pension scheme, 30 days annual leave allowance and a number of other benefits.

Developing Talent

We are committed to developing employees in their roles throughout their career. Learning and development plans enable employees to continue their professional development through training and development opportunities such as e-learning, classroom training and on-the-job experiences. We encourage our employees to share their learning across teams and organisations.

Equal Opportunities

We strive to make decisions based on individual merit and ability. We welcome applications from all sections of the community and promote equality of opportunity in accordance with the Equality Act 2010. As holders of Disability Confident Employer status, we guarantee to interview all applicants with disabilities who meet the minimum criteria for the vacancy.

As this job does not fulfil the Home Office Code of Practice criterion for obtaining sponsored migrant worker status we will be unable to apply for sponsorship for anyone not eligible to work in the UK. At interview, all shortlisted candidates are required to bring with them identification documents and original documents that prove they hold or can obtain the right to work in the UK. You can check your eligibility here: https://www.gov.uk/check-uk-visa/y.

Online applications only. Please submit a covering letter and CV ensuring that the IRC reference is included in the filename description of each document uploaded. Please note that failure to address the above criteria or submitted without a covering letter may result in your application not being considered.

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