Data Scientist/Senior Data Scientist

Company:
Location: Didcot

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Data Scientist/Senior Data Scientist

Science and Technology Facilities Council

Salary: £31,931 to £44,166 (dependent on qualifications and experience)

Plus a recruitment and retention allowance of up to £4,000 per annum

Contract Type: Permanent

Hours: Full time/Part Time (minimum of 25 hours a week)

Location: STFC Rutherford Appleton Laboratory, Harwell, Oxfordshire

Closing date: 22nd September 2021

About Us

At the Science and Technology Facilities Council (STFC), one of Europe’s largest multidisciplinary research organisations, the expertise of our computing staff is the key to making difference in research. STFC’s Scientific Computing Department (SCD) develops leading-edge software, computer, and data storage infrastructures, to support the work of world-class science both within STFC and internationally.

We work with the very latest technologies to advance science, particularly focussing on applied research. Whether it is the search for the Higgs Boson and dark matter, analysing climate data, or genomics, we address a number of the biggest and most challenging problems in scientific computing.

The Scientific Machine Learning (SciML) Group, situated within the Scientific Computing Department in RAL, works very closely with the large-scale experimental facilities, like Diamond Light Source, ISIS Neutron and Muon Source, Central Laser Facility, and Extreme Photonics Application Centre, and Centre for Environmental Data Analysis (CEDA) and their users, in applying and developing state-of-the-art AI and machine learning methods to translate their data into innovative science. The Group is also a ‘Turing Hub’ – a component of the Alan Turing Institute’s ‘AI for Science’ initiative.

With the advances in technology, these facilities 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, through to data curation, management, and archiving. As such, the SciML Group is seeking a number of positions to fulfil these roles, particularly from applicants with a strong background in machine learning or data science.

Work Programme

The successful applicant will be applying and developing novel and state-of-the-art machine learning (ML) and data analysis techniques to analyse large-scale experimental datasets collected with the view of advancing science.

These involve, not only applying and developing ML techniques, but also combining multiple datasets, improving the information extraction, visualising them, and most importantly working with scientists in understanding or characterising fundamental science.

Specific responsibilities include

  • PhD in computer science, electrical engineering, or relevant scientific subject area (mathematics, material science, physics, or life science) or equivalent experience
  • Experience in one of the following areas: Bayesian or probabilistic methods, machine learning, signal processing, data engineering, and visualisation
  • Experience in Python or other scientific programming languages (e.g., C/C++, FORTRAN)
  • Awareness of software engineering principles, with regard to robustness, portability, and usability
  • Good familiarity with one or more machine learning frameworks (e.g., SciKit Learn, TensorFlow, PyTorch, etc.)
  • Evidence of collaboration during software development and/or scientific research
  • Evidence of strong scientific communication skills (verbal, written, and presentation)
  • Ability to work both as part of a team, and with a high degree of autonomy
  • Able to travel in the UK and occasionally abroad

About you

The successful candidate will have:

Essential:

  • PhD in computer science, electrical engineering, or relevant scientific subject area (mathematics, material science, physics, or life science) or equivalent experience
  • Experience in one of the following areas: Bayesian or probabilistic methods, machine learning, signal processing, data engineering, and visualisation
  • Experience in Python or other scientific programming languages (e.g., C/C++, FORTRAN)
  • Awareness of software engineering principles, with regard to robustness, portability, and usability
  • Good familiarity with one or more machine learning frameworks (e.g., SciKit Learn, TensorFlow, PyTorch, etc.)
  • Evidence of collaboration during software development and/or scientific research
  • Evidence of strong scientific communication skills (verbal, written, and presentation)
  • Ability to work both as part of a team, and with a high deg

Desirable:

  • Experience in high performance (HPC) computing
  • Familiarity with reinforcement learning
  • Domain expertise in one of the following areas: Material, Life and Environmental Sciences, Astronomy, Particle Physics, and Laser Optics.

What we can offer you

By choosing to come and work at the STFC part of UKRI means that you will have access to a whole host of attractive benefits!

These include:

  • An exceptional index linked pension scheme,
  • 30 days leave (pro-rata) plus 10 public holidays,
  • Christmas shut down
  • Flexible working,
  • An onsite subsidised nursery
  • Access to employee shopping/travel discounts
  • Salary sacrifice cycle to work scheme.
  • Social and sporting activities and societies

We are committed to developing our staff, and training will be provided in relevant areas.

We are an equal opportunity employer and value diversity at our company.


About STFC


The Science and Technology Facilities Council is a world-leading multi-disciplinary science organisation where curiosity-driven, blue-skies thinking meets practical, application-led science and engineering. Our goal is to deliver economic, societal, scientific and international benefits to the UK and its people – and more broadly to the world.
One of Europe’s largest research organisations, we’re trusted to support, enable and undertake cutting-edge projects in an amazing diversity of fields. Through world-class facilities and people, we’re driving ground-breaking advances in science, engineering, computing and technology. Our research seeks to understand the Universe from the largest astronomical scales to the tiniest constituents of matter, yet creates impact on a very tangible, human scale.
For more information about STFC please visit https://stfc.ukri.org/
You can also visit our careers site https://www.stfccareers.co.uk/
How to Apply
Online applications only preferred for this role. Please submit your CV and a covering letter which clearly outlines how you fulfil the criteria specified along with your motivation to join STFC and the role you’re applying for. Ensure that the job reference number is included in the filename description of each document uploaded. Note that failure to address the above criteria or submit your application without a covering letter may result in your application not being considered. You will only be assessed on the content of your CV and covering letter and not the ‘experience’ section of the application.


About UKRI


Launched in April 2018, UKRI is a non-departmental public body sponsored by the Department for Business, Energy and Industrial Strategy (BEIS).


Our organisation brings together the seven disciplinary research councils, Research England, which is responsible for supporting research and knowledge exchange at higher education institutions in England, and the UK’s innovation agency, Innovate UK 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.


How we support EDI in the workforce


At UKRI we believe that everyone has a right to be treated with dignity and respect, and to be provided with equal opportunities to flourish and succeed in an environment that enables them to do so. We also value diversity of thought and experience within inclusive groups, organisations and the wider community. For further information, please visit ‘How we support EDI in the workforce’


Disability Confident Employer


As a Disability Confident employer, UKRI will offer an interview to a fair and proportionate number of disabled applicants that meet the minimum criteria for the job (this is the description of the job as set by the employer). To enable us to do this we ask the appropriate questions within the candidate application.
For more information on this scheme, click here.

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