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about 1 month ago
Science and Technology Facilities Council
Salary: £31305 - £43300
Location: Didcot
Job type: Permanent
Sector: Software Engineering
Category: Research & Development Jobs
Brief Description

Salary: £31,305- £34,028 (Band D) and £38,969- £43,300 (Band E)
Grade: D/E
Contract Type: Open-Ended
Hours: Full Time
Closing Date: 23rd October 2020
Interview Date: W/c 2nd November 2002

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 key to making our research happen. Consequently, we are committed to developing our staff, and training will be provided in relevant areas. We work with the very latest technologies to drive advances in both hardware and software that have genuine real-world applications. Whether it is the search for the Higgs Boson and dark matter, analysing climate data or genomics, our systems tackle the biggest and most challenging problems in scientific computing.

STFC’s Scientific Computing Department (SCD) develops leading edge software, compute, and data storage infrastructures, to support the work of world class science both within STFC and internationally.

As part of UK Research and Innovation, STFC offers a working environment and benefits package designed to provide an excellent work/life balance. For this opportunity, we welcome applications on a full-time, part-time (minimum 25 hours) or term-time only basis and we also offer a flexible working scheme. Further benefits include 30 days’ (pro rata) annual leave, 10.5 public and privilege days, Christmas shut down, a workplace nursery, an exceptional defined benefit pension scheme, and social and sporting activities and societies. STFC is an open and inclusive work environment, committed to promoting equality, diversity and inclusion.

Background

The Harwell campus of the Science and Technologies Facilities Council 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.

The Scientific Machine Learning (SciML) Group, situated within the Scientific Computing Department in RAL , works very closely with these large-scale experimental facilities, 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. The Group runs the PEARL AI computing service, powered by two, state-of-the-art NVIDIA DGX2 GPU systems, for Turing and STFC researchers, and their collaborators working on AI for Science.

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, through to data curation, management and archiving. As such, the SciML Group has been developing a number of AI solutions to the large-scale experimental facilities. The group is now seeking a data scientist / senior data scientist to help us deploying these solutions “at the edge” of these facilities. In other words, the position will focus on deploying machine learning solutions on the computing devices which are part of these large-scale facilities. Strong background in machine learning or data science, software engineering and skillsets for deploying Ai solutions on embedded AI devices is required. It is an exciting opportunity to change the way how technology impacts science.

Duties & Responsibilities:

You will ensure that AI solutions can be deployed within the compute units of the facilities. These compute units are considered to be “edge-devices”, and, as such, often limited in computational resources. It is in addition to developing / understanding state-of-the-art machine learning (ML) techniques for analysing operational datasets from facilities and detectors, you will also be contributing towards group’s core programme on benchmarking, and “AI at the Edge (or Edge AI)” . Specific responsibilities include:

* Developing ML or relevant techniques to transform datasets from detectors and facilities into a form that can be consumed by ML frameworks to be developed in the project
* Developing ML techniques to understand, interpret and extract features from these datasets
* Developing techniques to combine & fuse multiple data sources for better exploitation of information
* Working closely with the SciML team members, accelerator, beamline, detector and control teams to develop and suitable solutions
* Deploying AI solutions at the edge
* Contributing to learning and development at the Rutherford Appleton Lab, supporting its community by presenting work internally and externally, and by publishing work in peer-reviewed journals.

Contacts and Communication

* Regular contact with various teams, including operational, detector and technical teams at the facilities
* Regular contact with industries, such as hardware manufacturers
* Assist in organising and coordinating technical meetings and relevant project events as appropriate
* Maintain effective engagement with stakeholders.

Personal Skills and Attributes

* Strong communication skills (verbal, written, and presentation)
* Ability to work effectively under pressure, set priorities and make decisions independently
* Ability to work with uncertain requirements to develop a consensus on a plan of action
* High level of self-motivation and drive
* The ability to work as a team member delivering commitments on time
* A proven track record of analytical and problem-solving skills.

Further information

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For further information about this position please contact Jeyan Thiyagalingam (t.jeyan@stfc.ac.uk).

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.
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.

Shortlisting and Interview Criteria

Both Band D and E will have the following essential and desirable criteria.

Essential

* PhD in relevant scientific or computer science discipline or equivalent experience (S)
* Experience in a runtime efficient programming language (e.g. such as C/C++) (S&I)
* Awareness of software engineering principles, with regard to robustness, portability and usability (I)
* Experience in deploying solutions on resource-limited systems (S&I)
* Familiarity with one or more machine learning toolsets (e.g. SciKit Learn, TensorFlow, PyTorch, etc.) (S&I)
* Evidence of strong scientific communication skills (verbal, written, and presentation) (S&I
* Ability to work both as part of a team, and with a high degree of autonomy (I)
* Able to travel in the UK and occasionally abroad (I).

Desirable

* Experience of software development for data analysis for scientific problems (I)
* Evidence of algorithm development for scientific research (S&I)
* Experience on Edge AI (S&I)
* Experience with high performance computing (S&I).

In addition to these, applicants for the Band E position must meet the following essential criteria

* A PhD or equivalent professional experience in a field with relevance to data science (S)
* Deep understanding of managing, structuring, and analysing data, including building statistical models and using machine learning technologies (S&I)
* Strong leadership skills with previous experience of/the ability to lead, motivate and develop other (S&I).

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.

Polaris House is located next to Swindon Train Station and has excellent public transport links. Limited parking subject to waiting list.

Employee Benefits

UK Research and Innovation recognises and values employees as individuals and aims to provide a pay and reward package that motivates staff to the best of their ability. The reward and benefit package includes a flexible working scheme, an excellent Defined Benefit 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.

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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