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Postdoctoral Research Assistant in Learning Perceptive Contact-Rich LocoManipulation

On-site in Oxford·Full-time·Added today (last checked 28 Oct)

Our summary

Salary
£40,178 - £48,700 a year

About £2,700 - £3,220 a month after tax.

Work mode
On-site, Oxford
Contract
Full-time
Closing date
Apply by Wednesday 25 November

Skills

Requirements

What we're looking for

You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to manipulation and locomotion; path and motion planning, whole-body control, multi-contact manipulation/locomotion, machine learning and optimisation, avatar animation or related areas. You have experience working on real robots and great team working skills.

The role

We are seeking a full-time Postdoctoral Research Assistant to join the Machine Learning & Articulated Robots Group (ARG) of the Oxford Robotics Institute and the Department of Engineering Science in central Oxford. The post is funded by the EPSRC's Centre to Centre (C2C) Grant, "Mobile Robotic Inspector: Learning to Explore and Manipulate in the Real World" and is fixed-term for 24 months.

The project will develop leaning-based approaches to contact rich mobile manipulation (LocoManipulation) with a focus on legged robots -mainly humanoids- in challenging scenarios. This C2C project is in collaboration with ETH Zurich's "RobotX - Center for Robotics" and is build around a rich schedule of visits to and from ETH. The goal is to further develop our mobile manipulation capabilities, able of physically demanding and dexterous mobile manipulation tasks in a range of dynamic domains (industrial, service, domestic). This position will focus on using and developing learning-based perceptive approaches.

What you'll do

You will develop a control framework integrating multi-modal perception and tactile feedback, for locomotion and manipulation. You will be responsible for the design, development, implementation and evaluation of learning-based loco-manipulation methods suitable for legged systems in physically-realistic simulated environments and on real robots.

source_field: description

Informal enquiries may be addressed to Prof. Ioannis Havoutis.

For more information about working at the Department, see

www.eng.ox.ac.uk/about/work-with-us/

Keywords

Keywords: Humanoids, Machine Learning, Manipulation, Locomotion, Reinforcement Learning

Hiring process

Only applications received before noon (12.00pm GMT) on 25 November 2026 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.

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