Research Associate in Machine Learning

Full time: 35 hours per week

Fixed Term: for two years

The School of Informatics at the University of Edinburgh is inviting applications for a Research Associate in Machine Learning and Artificial Intelligence with a particular focus on method development for Planning in the context of diverse complex long-horizon settings. Two particular settings include event based planning (e.g. planning a trip) and forecast-based planning (e.g. allocating resources).

The Opportunity:

Real world planning is a complex process that needs to account for many stages that might be needed to execute a plan, significant uncertainties in the states that result from actions in a plan, and diverse sources of knowledge that contribute information relevant for plan formulation. Plan’s are made and changed dynamically. Furthermore it is not usually possible to interact with the environment extensively enough to learn a value function associated with state-actions.

Most reinforcement learning (RL) systems break in these circumstances. Yet humans are very able to make such plans. This project will attempt to move to these more realistic planning scenarios, by integrating systemic knowledge encoded in knowledge graphs, large language models for re-representing and formulating that knowledge, and world-modelling through forecasting to understand the scenario options. This will then prove a model-based environment as well as surrogate reward functions. These can be used via RL-like methodology to enable us to learn appropriate planners for particular scenarios. We will look at trip planning and load allocation as two example applications. 

This project is funded by Huawei UK is led by Amos Storkey along with Jeff Pan. The successful candidate will be based in the Informatics Forum, in central Edinburgh, and will work with colleagues in the Bayesian and Neural Systems Group and in collaboration with colleagues in Huawei Technologies Research & Development (UK) in Edinburgh.

The School of Informatics is one of the largest research centres in Computer Science in Europe, and it has been ranked #1 in the UK in terms of research power by a large margin. Informatics, Edinburgh is world renowned in Machine Learning, publishing in all the top venues in these fields. We are offering an exciting opportunity to work in an interdisciplinary, collaborative, friendly, and supportive environment, integrating different sub-fields of within Artificial Intelligence. 

We welcome both local (UK-resident) and international applicants. This position will include funding for international travel – e.g., for attending conferences, visiting research collaborators, and disseminating research findings. Furthermore, the researcher will have access to the computing infrastructure and office spaces available within Informatics and the research groups.

Your skills and attributes for success

• PhD (or near completion) or equivalent research experience in artificial intelligence, machine learning methods, machine learning systems or a very related discipline.
• Experience and evidence of effective independent research work within a research team, and contribution to the team effort. Evidence of ability to network and build collaborations.
• Demonstrated quality of research performance, as evidenced by high-quality publications in top-tier machine learning/computer vision/reinforcement learning and NLP venues (e.g., ICML, NeurIPS, ICLR, AISTATS, UAI, AAAI, ACL, EMNLP, ICCV, ECCV, CVPR), and relevant journals (IEEE PAMI, JMLR among others).

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