This new exciting post-doctoral Research Associate post, hosted at EEE at Imperial College London, is funded by the Advanced Research and Innovation Agency (ARIA) Nature Computes Better Opportunity Seed.This is for one of the agency’s first funded projects, aiming to redefine the way computers process information by exploiting principles found ubiquitously in nature.
The successful candidate will be integral to delivering on the project: “Brain-inspired spatially embedded neuromorphic networks with unprecedented memory”.There are two broad aspects to this project that the successful candidate would be working on. The first component will focus on building spatial and topological priors into state-of-the-art state space models, identifying the extent to which delay-based computation (in space) improve performance and/or energy/training efficiency. The second component, in collaboration with Intel (via the Intel Neuromorphic Research Community), will be to test these models on neuromorphic hardware – specifically Loihi2 chips. The scope of the project is wide, and we anticipate to pivot should new opportunities arise. We are open to a wide range of academic technical backgrounds but expect the candidate to start quickly. Machine learning/Neuro-AI experience is essential and a background in neuromorphic systems/hardware is highly desirable.
The successful candidate will work closely with the PI Dr Danyal Akarca (Imperial) and team Dr Daniel Goodman (Imperial) and Dr Jascha Achterberg (Oxford).Regular meetings will be conducted with the ARIA team. While an up to18-month post in the first instance, there is promising (although not guaranteed) opportunities for follow-on funding.
Yourresearch will be dynamic, with the scope to pivot and explore new opportunities as they arise, reflecting the innovative nature of the project.You willstart quickly and effectively, leveraging your experience in machine learning and Neuro-AI to contribute meaningfully from the onset.Youwill liaise with external collaborators and stakeholders to ensure the project’s success and alignment with broader research goals.Yourwill prepare and presenting research findings at academic conferences and in peer-reviewed journals.You willmentor other junior researchers and PhD students involved in the project, fostering a collaborative and educational environment.You willmaintain detailed documentation of research activities and outcomes to ensure reproducibility and transparency.You willstay up-to-date with the latest developments in relevant fields (machine learning, neuro-AI, and neuromorphic computing) integrating new knowledge into the project as appropriate.Yourrole may include contributing to the development of grant proposals and reports to secure additional funding and support for ongoing research initiatives.You willactively participate in departmental seminars, workshops, and other professional development opportunities to enhance your skills and knowledge.
Essential Requirements
PhD in a relevant field.You must hold a PhD in Computer Science, Neuroscience, Electrical Engineering, or a related discipline. You must hold a PhD in Computational Neuroscience, Computer Science, Neuro/AI, Machine Learning, Electrical Engineering, or a closely related discipline.
Machine learning expertise.Significant experience in advanced machine learning, training neural networks, constructing new architectures and learning objectives.
Neuro-AI knowledge.Strong background in Neuro-AI, with the ability to apply principles from neuroscience to AI models. For example, training networks in PyTorch on CPUs and GPUs.
Research experience.Proven track record of conducting high-quality research, as evidenced by publications and/or presentations at conferences.
Programming skills:Proficiency in programming languages commonly used in machine learning and neuroscience research, such as Python. Previous use of common AI/ML/optimisation libraries is essential (., PyTorch, Keras, JAX).
Project management:Experience managing research projects, including planning, execution, and reporting.
Mentorship.Ability to mentor and supervise junior researchers and PhD students, fostering a collaborative research environment.
Innovation.A creative mindset with a passion for exploring and implementing innovative research ideas.
Desired requirements
Neuromorphic systems.Familiarity with neuromorphic computing and hardware is highly desirable.
Funding applications.Experience in writing grant proposals and securing research funding is desirable.
The opportunity to work closely with the PI Dr Danyal Akarca (Imperial) and team, which includes Dr Daniel Goodman (Imperial) and Dr Jascha Achterberg (Oxford).The opportunity to work on one of ARIA’s first funded projects.The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.Grow your career: Gain access to Imperial’s sector-leading as well as opportunities for promotion and progression.Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
