Postdoctoral Research Assistant in Machine Learning

University of Oxford
February 28, 2024
Contact:N/A
Offerd Salary:£36,024 -£44,263
Location:N/A
Working address:N/A
Contract Type:fixed term for 12 mo
Working Time:Full time
Working type:N/A
Ref info:N/A
Postdoctoral Research Assistant in Machine Learning

Department of Engineering Science, Parks Road, Oxford, OX1 3PJ

We are seeking a full-time Postdoctoral Research Assistant to join the Foerster Lab for AI Research at the Department of Engineering Science, University of Oxford. The post is fixed term for 12 months and is funded by the UK Research and Innovation (UKRI).

This research project is focused on developing the foundations for artificial intelligence (AI) agents capable of supporting and collaborating with humans in complex, real-world settings. You will be responsible for researching and developing algorithms and techniques required to execute the project aims with a particular focus on the development and deployment of efficient and safe learning approaches for collaborative multi-agent reinforcement learning tasks.

You should have a PhD/DPhil (or be near completion) in machine learning or a closely related field. Knowledge of approaches for areas related to efficient, scalable, and robust deep reinforcement learning is essential as is an ability to manage own academic research and associated activities.

Informal enquiries may be addressed to Prof Jakob Foerster ([email protected]).

Only applications received before midday on the 28th February 2024 can be considered. You will be required to upload a covering letter/supporting statement, (describing how past experience fit with the advertised position), CV and the details of two referees as part of your online application.

Interviews are scheduled for the 12th and 13th March 2024

Contact Person : Prof Jakob Foerster Vacancy ID : 170810 Contact Phone : Closing Date & Time : 28-Feb-2024 12:00 Pay Scale : STANDARD GRADE 7 Contact Email : [email protected] Salary (£) : Grade 7: £36,024 -£44,263 per annum

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