Post-Doctoral Research Associate in Next-Generation Sensing using Event-Based Processing and Neuromorphic Computing

Updated: 3 months ago
Location: Edinburgh, SCOTLAND
Job Type: FullTime
Deadline: 16 Feb 2024

Heriot-Watt University has established a reputation for world-class teaching and leading-edge, relevant research, which has made it one of the top UK universities for innovation, business, and industry.

The School of Engineering & Physical Sciences has an international research reputation and close connection with the professional and industrial world of science, engineering, and technology. 

Job Summary

The PDRA will work as part of the Prosperity Partnership between Heriot-Watt University, the University of Edinburgh and Leonardo UK. This project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours of biological brains.

Detailed Description

In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have been shown to accelerate and improve the training procedure of SNNs by defining new cost functions that are differentiable and easier to optimize.

Key duties and responsibilities

The post holder is required to:

  • General tasks will involve scientific research; analysis and interpretation of data; daily oversight of the activities of postgraduate and undergraduate project students in the laboratory; communication with other investigators involved in this collaborative project; preparation of scientific papers; presentation of research at conferences whilst also supervising the activities of junior group members and PhD students. 
  • Contribute to experimental design and procedure as part in a collaborative decision-making process, while taking responsibility for implementing experiments, theoretical models and data analysis. 
  • Assistance in the day-to-day maintenance of the experimental facilities, liaising with external collaborators, assisting in the development of student research skills, and contributing to teaching (lab and tutorial demonstrations) in relevant taught courses within Engineering. 
  • Be involved in our outreach activities, with roles that can be tuned to the specific preferences of the candidate but will involve for example interviews, talks for the public and preparation of experimental demonstrators for use in schools. 

 Essential Criteria 

  • A PhD in a relevant area of Engineering, Mathematics, Physics, or related subject (or a thesis submitted by the start date of the position). 
  • Ability to articulate research work, both in written technical reports / papers and by oral presentation. 
  • Proven academic ability and a demonstrable high level of technical competence in computational data science and the analysis / modelling of the results. 
  • Theoretical or experimental experience of in an area of direct relevance to the project. 
  • Ability to formulate and progress work on their own initiative with evidence of research ability: problem solving, flexibility.
  • Able to work as part of a team at Heriot-Watt out with the specific project and more widely with the collaborators at other Universities. 

Heriot-Watt University is committed to securing equality of opportunity in employment and to the creation of an environment in which individuals are selected, trained, promoted, appraised and otherwise treated on the sole basis of their relevant merits and abilities.  Equality and diversity are all about maximising potential and creating a culture of inclusion for all.

Heriot-Watt University values diversity across our university community and welcomes applications from all sectors of society, particularly from underrepresented groups. For more information, please see our website https://www.hw.ac.uk/uk/services/equality-diversity.htm  and also our award-winning work in Disability Inclusive Science Careers https://disc.hw.ac.uk/ . 



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