University College London (UCL), Mathematics

Position ID: 1002-RESFELL [#14515, 1821870]
Position Title: Research Fellow
Position Type: Postdoctoral
Position Location: London, London, City of, United Kingdom [map]
Subject Areas: mathematics, mathematical sciences, mathematical modelling
Application Deadline: 2019/10/15 (posted 2019/09/18, listed until 2019/10/15)
Position Description:    

UCL Department of Mathematics

London

Research Fellow

Full Time:

The appointment will be on UCL Grade 7.

The salary range will be £35,965, inclusive of London Allowance.

Applications are invited for a full-time Research Fellow position to work with Dr Hao Ni on the project Human Computer Interfaces. The position is funded by the EPSRC as part of the Programme Grant Unparameterised multi-modal data, high order signatures, and the mathematics of data science (DATASIG) and will be part of a multi-university research group (Imperial College London, University College London, and University of Oxford) with a hub at the Alan Turing Institute. This position will be based at the Alan Turing Institute, British Library, and the successful applicant will be embedded beside the software engineering team at the Alan Turing Institute.

Through a collaboration between leading mathematicians and leading domain scientists, the Programme will create a powerful and generic set of mathematical and computational tools for the analysis of complex multimodal data streams and to establish their effective use in four applied challenges (ACs): Mental Health, Radio Astronomy, Human Machine Interfaces and Computer Vision. Each area will be supported by at least one PDRA. Other PDRAs will focus on the underlying mathematics. The department has internationally recognised research groups in pure and applied analysis; fluid mechanics; mathematical physics; geometry and topology; algebra, number theory and combinatorics; mathematical modelling in biology, finance, industry and society. The successful applicant will work closely with Dr Hao Ni (Co-I Maths, UCL), and the Project Partner Lianwen Jin from South China University of Technology (SCUT) focusing on core challenges in Human Computer Interfaces. Smart devices should be intelligent interpreters that collect requests, digest information and return valuable responses, eventually transforming how people live and work. The human computer interaction (HCI) experience with these devices will be critical in determining the nature of that interaction. We focus on three kinds of intelligent HCI technologies for such devices, namely, handwriting-based HCI, accelerometer based HCI and egocentric gesture-based HCI. These three kinds of HCI share the common characteristic that they are all based on interpreting multidimensional sequential data accurately in real time with a large (or huge) number of outcomes.

The post-holder will spend roughly three days per week in the department of Mathematics, UCL, and the rest of time in London at the Alan Turing Institute and will actively and enthusiastically engage with Terry Lyons (PI, Oxford), Thomas Cass (Co-I, Imperial), and Harald Oberhauser (Co-I, Oxford), with the PDRAs in the wider DataSig Team, with the software engineer and, where appropriate, with other project partners.

This post is funded for 48 months in the first instance. T he post-holder is expected to spend one year in Professor Lianwen Jin’s team as a secondment. This post is available from 1 November 2019 or as soon as possible thereafter.

Candidates should either have a PhD or equivalent qualification in Mathematics or field related to the Programme, or should be finalising their PhD or waiting for their viva date.

Please note: Appointment at Grade 7 is dependent on award and confirmation of a PhD (or equivalent). If this is not the case, initial appointment will be at Research Assistant Grade 6B, point 26 (salary £32,607 per annum inclusive of London allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

We are looking for a strong candidate with a solid mathematical background, strong programming skill and a high level of experience in modern data science. The candidate should have a track record in mathematics/machine learning/computer vision or related areas. The data is likely to be complex and extracting actionable information challenging, so it is important that individual also have the ability to distinguish and prioritize the possible questions on the basis of their theoretical contribution and the practical constraints of the information available. The successful candidate is expected to have some expertise and research experience in rough path theory and related areas. Candidates will also have be required to have proficiency in scientific programming, and excellent communication skills, both written and oral. Strong interpersonal skills, and knowledge of aspects of nonconforming finite element methods and level set methods, are also desirable. As a Department policy, the successful candidate will be required to teach one undergraduate course per year, writing and marking examinations, and carry out duties of 2nd examiner.

UCL vacancy reference: 1821870

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button above.

If you have any queries regarding the vacancy or the application process, please contact Adrianna Mickiewicz ( a.mickiewicz@ucl.ac.uk ).

Informal enquiries may be addressed to Dr Hao Ni, email h.ni@ucl.ac.uk

Closing Date: 15 October 2019

Latest time for the submission of applications: 23:59.

Interview Date: TBC

UCL Taking Action for Equality

We will consider applications to work on a part-time, flexible and job share basis wherever possible.

Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality.

To apply click here https://atsv7.wcn.co.uk/saf/login.cgi?SID=b3duZXI9NTA0MTE3OCZleHRlcm5hbD0yNDc4NTUmamNvZGU9MTgyMTg3MCZvd25lcnR5cGU9ZmFpcg==1821870


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University College London
Department of Mathematics
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