Research Associate (fixed-term post)

Job title Research Associate (fixed-term post)

Department Mathematical Sciences

Salary Starting from £33,797, rising to £40,322

Grade Grade 7

SOC Code - Visa Requirements 2119

Placed on Monday 14 December 2020

Closing date Sunday 31 January 2021

Interview date See advert

Reference CC8003

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We invite applications for a Research Associate on the EPSRC-funded project "Multiscale Machine Learning At the Edge", led by Dr. Matthew Nunes

Machine learning has opened up exciting avenues of research in technology, computer science and mathematics.  Learning is commonly performed with cloud-based computing, in which processing is performed centrally before updating individual contributing devices. However, this costs a lot of time and energy in data transfer, and with potential data security risks.  With more tasks being required on personal devices, there is a need to devise new machine learning algorithms suitable for such settings.

On this exciting project you will undertake, under the guidance of Dr. Nunes, cutting-edge research to develop new methodology to tackle machine learning challenges under resource constraints. The aim will be to combine novel statistical signal processing methods with state-of-the-art learning techniques to drive algorithm efficiency. Methodological challenges will centre around tailoring learning methods to different data types and ensuring robustness in the face of data dropout due to sensor failure. We will focus on applications common on 'edge' devices, such as activity monitors and low-powered tablets.  You will be expected to disseminate the results in leading academic journals and conferences.

You are expected to hold, or be about to receive, a PhD degree in statistics, signal processing, machine learning or a related discipline. A specialism in developing novel computational or theoretical contributions is essential. Expertise in frequency-domain or wavelet-based techniques is highly desirable. Programming experience in R, Python or equivalent languages is also required. You will be expected to learn quickly, engage with new ideas, and contribute new insights.

This position is on a full-time basis (36.5 hours per week), for a fixed-term period of up to 20 months. For further information and an informal discussion about the role please contact Dr. Matthew Nunes (m.a.nunes@bath.ac.uk).

Applications should include:

  • an up-to-date curriculum vitae,
  • a one-page research statement describing your research interests, your experience in the area of the position and your career aspirations.

Interviews are likely to take place w/c 15 February 2021.

As a member of the project team, you will join the research group in Statistics within the Department of Mathematical Sciences.  The group has considerable expertise in a number of areas, including clinical trials, computational statistics, graphical models and network analysis, machine learning, spatial statistics and time series.  The group forms part of the University of Bath's Centre for Mathematics and Algorithms of Data (MAD), an initiative together with the Department of Computer Science, to foster research across traditional boundaries.  The successful candidate will be able to participate in research activities across the centre.

The Department has over 70 academic staff representing all areas of Mathematics.  Our Department emphasises the unity of Mathematics and there are strong interactions between research groups. Impact is achieved through a wide variety of interdisciplinary research projects, and industrial collaborations. These activities are supported by the Centre for Doctoral Training in Statistical Applied Mathematics at Bath (SAMBa), which has currently over 70 PhD students and an annual intake of 10-20 research students. The research associate would be encouraged to participate in these activities – these would provide further opportunity for applied and statistical mathematics training and broadening of the associate's research experience.

In addition, the Bath Institute for Mathematical Innovation (IMI), promotes, and supports, cross-campus research activities, industrial, and international collaborations, in all areas of mathematics and statistics. Various research centres such as the Centre for Mathematical Biology, the Centre for Networks and Collective Behaviour, and the Centre for Nonlinear Mechanics, provide focus in interdisciplinary collaborations. The department is committed to providing a supportive research environment, aiming to bring about positive cultural change in diversifying recruitment of early-career academics.

We recognise the commitment, achievements and talents of our workforce through our offering of initiatives and benefits, including (but not limited to): 

  • Generous employer pension contributions
  • 39 days holiday (annual leave, discretionary days and bank holidays)
  • A flexible working environment
  • A commitment to personal and professional development
  • Ofsted outstanding rated onsite nursery
  • Salary exchange scheme (cycle to work)
  • Onsite private and NHS dentist, onsite medical centre
  • Employee discount scheme

We value, promote and celebrate inclusion, challenging discrimination and putting equality, diversity and belonging at the heart of everything we do. We aim to be an inclusive university, where difference is celebrated, respected and encouraged. We truly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and students, creating a learning environment and organisational culture that enhances health and wellbeing across our community. We are very proud to have recently received Ambassadors for Autism certification and are an accredited Disability Confident Leader (level 3); committed to building disability confidence and supporting disabled staff.

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Further details:

If you think you may require a visa to work in the UK you should refer to our applicant information webpage  before embarking on a job application to ensure that you understand the requirements for sponsorship. You may be eligible to work in the UK via other alternative visa routes such as the Global Talent Visa or by having Settlement / ILR, please refer to our Staff Immigration webpages for further details.

The University of Bath is an equal opportunities employer and has an excellent international reputation with staff from over 60 different nations.  We have made a positive commitment towards gender equality and intersectionality receiving a Bronze Athena SWAN award, and we are actively working towards a Silver award. We are a family-friendly University, with an increasingly agile workforce. We are open to flexible working arrangements and we’re also proud to be a disability confident employer and are happy to discuss any reasonable adjustments you may require.