Research Associate in Neuromorphic Computing Algorithms

Job description

We are seeking a highly motivated and conscientious post-doctoral researcher to join a very collaborative, interdisciplinary, and friendly research group at King's College London led by Dr Bipin Rajendran.

The successful candidate will work on the EPSRC Open Plus Fellowship awarded to Dr Rajendran that focuses on creating a smarter and greener AI. The focus of this researcher will be on developing novel event-driven AI algorithms for trustworthy decision-making motivated by the free energy principle. They will also work in parallel with another researcher who will be building nanoscale devices based on 2D materials and pursue the novel approach of using the undesirable imperfections of nanoscale devices as a resource for efficiently implementing free energy-based AI algorithms in hardware.

The post will be based in the Department of Engineering.  The department is located at the Strand campus of King's, located in the centre of London.

The successful candidate should have a PhD in Neuroscience/Computer Science/Electrical Engineering and they should meet the following criteria

• Background or understanding of the free-energy principle
• Background in machine learning or brain-inspired, spike-based neuromorphic computing
• Track record of high-quality research publications in peer reviewed conferences and journals.

For an informal discussion to find out more about the role please contact Dr. Bipin Rajendran via email at bipin.rajendran@kcl.ac.uk.

This post will be offered on a fixed-term contract for 2.5 years

This is a full-time post - 100% full time equivalent

Key responsibilities

Carry out research on design, emulation, and benchmarking of novel event-driven AI algorithms inspired by the free energy principle.

Write papers and technical reports

Present research at conferences and external audiences including funding bodies

Work with PhD students to fulfil the objectives of the project

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria

1. Background in free energy principle or machine learning or neuromorphic computing
2. Track record of high-quality research publications in peer reviewed journals or conferences
3. Knowledge of Python or other similar programming languages
4. Research independence

Desirable criteria

1. Familiarity with Bayesian learning
2. Familiarity with hardware acceleration of AI algorithms

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