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伦敦大学学院
About us
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 the University of Oxford) with a hub at The Alan Turing Institute. This position will be based at University College London and 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 Research Fellow. Other Research Fellows will focus on the underlying mathematics.
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.
Candidates should either have a PhD or equivalent qualification in mathematics, or a field related to the programme, or should be finalising their PhD or waiting for their viva date. The successful candidate will have research experience in in rough path theory and related areas, clear evidence of outstanding promise and originality in research, with a good publication record, commensurate with career stage. Ability to identify, develop and apply concepts, techniques and methods in new contexts, keep accurate records of research results and activity, help with reporting. As well as the ability to exercise initiative and judgement in carrying out research tasks, conduct a detailed review of recent literature, and organise own work independently and prioritise in response to deadlines. They will demonstrate willingness and ability to work effectively with a team of researchers and across disciplines to contribute towards the programme’s aims and objectives by actively engaging with the broader programme team, and have excellent communication skills, both written and oral.
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 £34,976 per annum inclusive of London allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.
41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days)
Additional 5 days’ annual leave purchase scheme
Defined benefit career average revalued earnings pension scheme (CARE)
Cycle to work scheme and season ticket loan
Immigration loan
Relocation scheme for certain posts
On-Site nursery
On-site gym
Enhanced maternity, paternity and adoption pay
Employee assistance programme: Staff Support Service
Discounted medical insurance
Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.
https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?jobId=823&jobTitle=Research%20Fellow
实习内推
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高校招生
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