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Position: Research Fellow in Reinforcement Learning
Institution: University College London
Department: Centre for Advanced Spatial Analysis (CASA)
Location: London, United Kingdom
Duties: This role will involve the development of new models of human behaviour through Deep Reinforcement Learning and Inverse Reinforcement Learning, with a view to integrating these models within Agent-based Simulation of urban phenomena. The RL models to be built during this project will integrate inputs from non-stationary 3D urban environments, yielding learning models that reasonably represent observed human behaviour and crowd dynamics. RL models will be built for a variety of scenarios and behaviours, but a primary focus will be on modelling urban movement behaviour and emergent crowd phenomena, integrating aspects of uncertainty and population heterogeneity
Requirements: A PhD (awarded or nearing completion) in Reinforcement Learning, Agent-based Modelling, Multiagent Systems, Cognitive Science, Mathematics, Computer Science, GIScience, or related area. Deep knowledge of a programming language for data science, modelling and visualisation (e.g. Python, R, or other relevant approach). Experience of applying machine learning and modern data science methods in analysing spatial and/or behavioural trends
   
Text: Research Fellow in Reinforcement Learning, - Ref:1793234 Click here to go back to search results Apply Now UCL Department / Division Centre for Advanced Spatial Analysis (CASA) Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?35,328-?42,701 per annum Duties and Responsibilities Advances in Reinforcement Learning offer new opportunities for modelling human behaviour in a variety of spatial contexts. This role will involve the development of new models of human behaviour through Deep Reinforcement Learning and Inverse Reinforcement Learning, with a view to integrating these models within Agent-based Simulation of urban phenomena. The RL models to be built during this project will integrate inputs from non-stationary 3D urban environments, yielding learning models that reasonably represent observed human behaviour and crowd dynamics. RL models will be built for a variety of scenarios and behaviours, but a primary focus will be on modelling urban movement behaviour and emergent crowd phenomena, integrating aspects of uncertainty and population heterogeneity. The work will draw on a variety of large spatiotemporal trajectory datasets, collected both in urban and virtual environments. The role will involve developing partnerships with colleagues at the Turing, UCL, other collaborating universities, and industrial partners. We are seeking a Research Fellow to undertake this research. The role is available on a full-time basis for eighteen months. This project is conducted in partnership with The Alan Turing Institute (ATI). The Alan Turing Institute is the national institute for data science and artificial intelligence, with headquarters at the British Library. A core mission of the Turing to undertake and promote research into data science and artificial intelligence. UCL is a founding university partner of the institute and remains a closely engaged in activities at the Turing. The Turing is supporting this project through a Fellowship and Project funding lasting until October 2020 and is positioned within the Urban Analytics programme. Further details about the Turing and its activities can be found at: www.turing.ac.uk . Key Requirements A PhD (awarded or nearing completion) in Reinforcement Learning, Agent-based Modelling, Multiagent Systems, Cognitive Science, Mathematics, Computer Science, GIScience, or related area. Deep knowledge of a programming language for data science, modelling and visualisation (e.g. Python, R, or other relevant approach). Experience of applying machine learning and modern data science methods in analysing spatial and/or behavioural trends. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ?Apply Now? button below. If you have any queries regarding the vacancy or the application process, please contact Dr Ed Manley ed.manley@ucl.ac.uk . UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 23 Mar 2019 Latest time for the submission of applications 23:59 Interview date TBC This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job description and further details Apply Now
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