Post-Doctoral Research Associate in Machine Learning for Autonomous Alignment

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

This is an integrated part of the on the project “Robotic Assembly and Maintenance” which, itself is part of the “Manipulation Challenge” of the “Smart Products Made Smarter” (EPSRC funded EP/X025365/1) Prosperity Partnership between Heriot-Watt University, University of Edinburgh, and Leonardo UK.

Detailed Description

This post is part of a major project that is focused on automating such alignment processes using either, or both, robotic or mechatronic alignment.

These processes will be driven by advanced optimisation and ML approaches employing arrange techniques such as: transfer and reinforcement learning, supervised and unsupervised methods, and classical and multi-objective optimisation.

Equally important to the focus on ML algorithms is the development of adaptive, possibly human-inspired, strategies for leaning complex muti-step alignment processes.

Key duties and responsibilities

The post holder is required to:

• 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 and preparation of scientific papers.
• Contribute to experimental and theoretical 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 in relevant taught courses within Physics and Engineering. 

Essential Criteria 

Applicants must have:

• Applicants should hold a PhD in a relevant area of Physics, Computer Science, or related subject (or a thesis submitted by the start date of the position). 
• Ability to articulate research work via written technical reports, academic publishing and by oral presentation. 
• Must have proven academic ability and a demonstrable high level of technical competence in machine learning and/or optimisation systems. 
• Theoretical or experimental experience in an area of direct relevance to the project (i.e. machine learning, systems optimisation). 
• Ability to formulate and progress work on their own initiative with evidence of research ability: problem solving, flexibility.
• Must be able to work as part of a team on the experiments at Heriot-Watt in Edinburgh out with the specific project and more widely with the collaborators of the project. This appointment is in partnership with Leonardo and is conditional upon you being able to demonstrate eligibility for UK Security Clearance.

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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