Research Associate in Hardware Acceleration for Machine Learning
Computer Science,Computer Science,Engineering and Technology,Electrical and Electronic Engineering
Short info about job
Company: University of Cambridge
Department: Computer Laboratory
Salary: £30,175 to £38,183
Hours: Full Time
Contract type: Fixed-Term/Contract
Type / Role: Academic or Research
Phone: +44-1342 7481109
Fax: +44-1355 6214111
E-mail: N\A
Site: N\A
Detail information about job Research Associate in Hardware Acceleration for Machine Learning. Terms and conditions vacancy
Department/Location: West Cambridge
The funds for this post are available until 30th April 2020 in the first instance.
The Computer Laboratory is seeking a Research Associate to join a project exploring the design of neural networks and hardware for machine learning applications. The project is part of a larger collaboration with industry and other world-leading machine learning and computer architecture research groups. The goal of the project is to develop and evaluate novel accelerator architectures for machine learning applications and to develop new theory and techniques to support practical on-device learning. The successful candidate will join an enthusiastic group of researchers already working on various projects in this area.
We seek candidates with a strong background in Computer Science and an interest in machine learning and computer architecture. We welcome candidates from a wide-range of backgrounds, including those with an interest in network-level challenges, such as continual or incremental learning, and those whose primary focus has been hardware accelerator design.
Candidates should hold a PhD or have equivalent experience. Candidates who are close to submitting a PhD will also be considered.
Applicants should contact Dr Robert Mullins ([email protected]) for further information.
To apply online for this vacancy and to view further information about the role, please visit:
www.jobs.cam.ac.uk/job/14774. This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form.
Please ensure you upload your Curriculum Vitae (CV) and a covering letter. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please quote reference NR13118 on your application and in any correspondence about this vacancy.
The University values diversity and is committed to equality of opportunity.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.