英国利兹大学所博士后职位—移动数据科学

2023年11月16日

来源：知识人网整理

摘要：

英国利兹大学所博士后职位—移动数据科学

利兹大学（University of Leeds），是一所位于英国利兹的公立综合研究型大学，是世界百强名校、英国红砖大学。

利兹大学是罗素大学集团，世界大学联盟、国际大学气候联盟、欧洲大学协会、英联邦大学协会、中英大学工程教育与研究联盟、RENKEI 、N8大学联盟、白玫瑰大学联盟成员。

利兹大学的前身是成立于1874年的约克郡科学院，1884年与利兹医学院（成立于1831年）合并为约克郡学院，1887年与欧文斯学院（曼彻斯特大学的前身）和利物浦大学学院（利物浦大学的前身）组建联邦制维多利亚大学。1904年爱德华七世颁布皇家宪章，正式成立利兹大学。

利兹大学位列2024QS世界大学排名第75位。

Research Fellow in Mobility Data Science

University of Leeds

Job Description

Are you an ambitious researcher interested in human mobility behaviour? Are interested in pushing forward the state-of-the-art in mobility data science, through large-scale mobility data? Do you want to further your career in one of the UK's leading research-intensive Universities?

We are delighted to be recruiting two new two-year Research Fellows in Mobility Data Science to work on the cutting edge of human mobility analysis. The Research Fellows will use large-scale mobility data, in combination with machine learning and statistical measures, to answer critical questions about the nature of mobility behaviour and its role within wider social and spatial systems.

The Research Fellows we recruit will work closely with each other, and join an active, ambitious, and interdisciplinary research group of other Fellows and PhD students, all working on mobility challenges at different scales and contexts. Our recent research has explored how mobility data and models can derive new insights into health, sustainability, human cognition, inequalities, and economic activity. While there are commonalities in the requirements and approaches required of the two posts, they relate to and will have responsibility for one of two distinct projects.

Post 1 (Indoor Movements and Interactions)

Working with mobility data collected within a large hospital environment, to understand patterns of movement, activity, and interaction. The research will make advances to the state-of-the-art in trajectory analysis, drawing in methods from machine learning, and developing novel approaches to deal with uncertainty, privacy protection, production of synthetic data, and ensuring data reliability. The postholder will have opportunities to work with data from a variety of sources, including Bluetooth sensors and routinely collected activity records. There will also be opportunities to develop linkages between mobility and health-related data (e.g. infections, virology), opening opportunities to identify patterns of infection transmission over precise space and time. The research is funded through the EPSRC i-sense and Digital Health Hub projects, and will involve close collaboration with partners at University College London, University College Hospital, and University of Sheffield.

Post 2 (Urban Navigation)

The post will focus on the development of novel predictive models of urban spatial navigation. The project will make use of large-scale real-world trajectory data in combination with machine learning and the theory of spatial cognition, to derive theoretically and scientifically robust models of movement. The project is expected to make high-impact contributions in mobility behavioural research. As such, it is expected that the Research Fellow will be comfortable with concepts from the broad literature around mobility and/or navigation behaviour, and be confident in translating these ideas into computational models. This research is funded by the Leverhulme Trust and the Alan Turing Institute, with whom there will be regular interaction.

Both posts will be based in Professor Ed Manley's research group, located between the School of Geography and Leeds Institute for Data Analytics (LIDA). As members of an active research group, based at a major research-intensive University, the post holders will have ample opportunities to develop their research skills, build interdisciplinary collaborations, and contribute world-leading mobility research.

Professor Ed Manley, Professor of Urban Analytics and Pro-Dean for Research and Innovation

Email: e.j.manley@leeds.ac.uk

Location: Leeds - Main Campus

Faculty/Service: Faculty of Environment

School/Institute: School of Geography

Category: Research

Grade: Grade 7

Salary: £37,099 to £44,263 p.a.

Working Time: 100% - We will consider job share / flexible working arrangements

Post Type: Full Time

Contract Type: Fixed Term (24 months)

Release Date: Wednesday 08 November 2023