Lecturer or Senior Lecturer in Artificial Intelligence/Machine Learning

The Department of Computer Science seeks to strengthen and expand its research in AI & Machine Learning through the appointment of a Lecturer or Senior Lecturer in AI/Machine Learning. The successful candidate will be expected to grow a world-leading research portfolio in an area of their choice, contributing to fundamental advances in AI theory and innovative applications across a wide range of domains.

You will be responsible for:

• Undertaking and directing original research of the highest international standard in the area of AI/Machine Learning.

• Developing national and international research collaborations.

• Obtaining substantial grant and other research income to fund a growing research effort.

• Actively contributing to and enhancing the teaching programmes of the Department of Computer Science at both undergraduate and postgraduate levels.

The role offers scope to develop research in areas including, but not limited to, causal modelling, reinforcement learning, game theory, AI for Science, AI with human-in-the-loop, decision-making for complex systems, optimisation for LLMs, foundation models, dimensionality reduction, deep learning, uncertainty quantification, language, and developmental robotics.

About You

The Department is looking for an enthusiastic and self-motivated researcher and teacher to join a dynamic group of scientists. You should demonstrate:

Essential Criteria

• A PhD or equivalent (including industrial) experience in AI/Machine Learning.

• A record of high-quality publications in the best AI/ML outlets, such as ICML, NeurIPS, AISTATS, JMLR, PAMI, ICLR, IJCAI, AAAI, UAI.

Desirable Criteria

• Demonstrated ability to obtain research funding and to manage research projects.

We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.

Our benefits include:

• Generous employer contribution pension

• 29 days annual leave plus bank holidays, along with Christmas closure

• Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.

Enquiries about the role, shortlisting and interviews

Name: Andrew Stewart

Email Address: Andrew.J.Stewart@manchester.ac.uk

General enquiries and administrative support

recruitmentservices.people@manchester.ac.uk

Technical and job portal support

https://jobseekersupport.jobtrain.co.uk/support/home

Applications close at midnight on the closing date.

Further particulars (with person specification) linked below.

This listing was sourced from 4dayweek.io.