[robotics-worldwide] [jobs] Postdoctoral fellow at Aston University, UK: Deep Reinforcement Learning & Knowledge Transfer for Manipulation (CHIST-ERA InDex Project)

Faria, Diego d.faria at aston.ac.uk
Mon Mar 25 03:50:32 PDT 2019

Postdoctoral Fellowship: Deep Reinforcement Learning & Knowledge Transfer for Robot Dexterous In-Hand Manipulation

Applications are invited for a Postdoctoral Fellowship at the School of Engineering & Applied Science to be undertaken within the Computer Science Group at Aston University, Birmingham, UK. The successful applicant will join an established experimental group working on artificial perception and machine learning towards robot dexterous manipulation. This position is available to start as soon as possible.

The postdoctoral fellow will work within the EU CHIST-ERA InDex project (Robot In-hand Dexterous manipulation by extracting data from human manipulation of objects to improve robotic autonomy and dexterity) that will kick-off in April 2019. It is expected the fellow will collaborate with our partners (Sorbonne University, Technische Universität Wien, University of Genoa, and University of Tartu) during the course of the project.

This post is initially one-year contract, with the possibility of renewing it until the duration of the project (3 years).

Background of the Project
It is expected that the postdoctoral fellow will contribute to the design and development of an approach based on deep reinforcement and transfer learning to endow a robot (anthropomorphic robotic hand) to autonomously learn and adapt its strategy to interact with objects during in-hand manipulation tasks, and also being able to transfer this knowledge to other contexts. Beyond of learning from human demonstrations, learning from a synthetic environment (simulations) can be an alternative, where transfer learning will play an important role to use the knowledge acquired from simulation to apply to a real-world context.

Financial Support
The fellowship is based on Aston University (UK) Grade 8 spine point 32, which is currently a salary of £35,211 per annum, with adjustment every year (April).

Person Specification
The successful applicant must have a Ph.D. degree in Computer Science or Electrical Engineering or other related areas.  Preferred skill requirements include experience with robot perception, grasping and dexterous manipulation and/or knowledge of machine learning.
We would particularly like to encourage application from women seeking to progress their academic careers. Aston University is committed to the principles of the Athena SWAN Charter, recently recognised by a prestigious Silver Award to the School of Engineering & Applied Science, and we pride ourselves on our vibrant, friendly and supportive environment and family atmosphere.

How to Apply (Deadline: until the position is filled – we encourage early submissions)
Submissions will only be accepted through the online system. Access the application form at https://urldefense.proofpoint.com/v2/url?u=https-3A__jobs.aston.ac.uk_Vacancy.aspx-3Fref-3DR190097&d=DwIF-g&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=90cCdT0eua6gHLxoBXy_7h9MBd2qx9pzV66Ih_2DBec&s=6vw-PdUS938SIjYcOMM5qxzT3T6gznbpEAARMvRDESk&e= (at the bottom of this page access the link: Apply Online), fill the form and attach your Motivation Letter, CV with your full list of publications, Research Statement (no more than 2-3 pages), and 2 names for references.

Note that, submissions without these documents will not be considered. For informal  inquiries, feel free to contact Dr Diego R. Faria (project coordinator) d.faria at aston.ac.uk<mailto:d.faria at aston.ac.uk>  or Dr George Vogiatzis (Co-PI) g.vogiatzis at aston.ac.uk<mailto:g.vogiatzis at aston.ac.uk> .

Shortlisted applicants will be invited for an interview (ideally between 29/03 and 10/04/2019).

Best Regards
Diego R. Faria

Dr Diego Resende Faria
Lecturer (Assistant Professor) in Computer Science
School of Engineering & Applied Science
Aston University, Birmingham, B4 7ET, UK
Room MB 211-D,  Tel: +44 (0) 1212 044 868

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