Global Chair in Machine Learning

Lincoln, Lincolnshire (GB)
Monday, 7 January 2019
End of advertisement period
Friday, 8 February 2019
Contract Type
Full Time

As a TEF-Gold rated institution, the University of Lincoln is ranked 22nd in the UK in the Guardian University Guide and 42nd in The Times and Sunday Times Good University Guide. As part of a Global Chairs campaign, and to invest further in research leadership where we know we can make a significant difference, the University now seeks to appoint a Global Chair in Machine Learning as part of its Global Chairs Campaign.

Suitable candidates will possess significant academic standing and accomplishment in the field, as well as the vision, leadership, experience and enthusiasm to make a real impact in building and advancing research activity at the University in this area. Enhancing our growing strength in Machine Learning, we are creating a Chair in this area which will align well with our existing structures, and rapidly growing Machine Learning Group.

We understand that research is at the heart of what it means to be a university. We are proud to be home to world-class researchers who are making significant contributions to their subject areas. This was reflected in the latest Research Excellence Framework, where more than half of the University’s research was rated as world-leading or internationally excellent.

We are a fast-growing university, where staff and students work collaboratively on pioneering research that makes a tangible difference to people’s lives. Our researchers are tackling some of the world’s most challenging problems, from the fight against drug-resistant bacteria to mitigating the impact of climate change.

The School of Computer Science is based on our picturesque waterfront Brayford campus and benefits from state-of-the-art facilities in the Isaac Newton Building. The School holds a broad range of expertise in Computing Technologies and Information Systems, including specialisms in robotics and autonomous systems, computer vision and image engineering, medical applications of technology, social computing, games computing, cultural computing and business computing.

The research interests of the Machine Learning group cover a variety of subfields where machine learning meets data science, intelligent systems, knowledge representation and reasoning, multimedia and multimodal content analysis, indexing and retrieval, semantic metadata interoperability and search, behaviour recognition and affective interactions, sentiment analysis, as well as applications in medical data analysis and health care monitoring, cultural content search and digital libraries, computational finance, computational advertising, smart homes, smart cities and Internet of Things.

The University has engaged Perrett Laver to support the University in this appointment process and further information can be downloaded from our website at For informal enquiries about the role, please email Nataliya Mykhalchenko at, quoting reference number 3886/4.

Applications should consist of a letter of application together with a curriculum vitae and a publications list. 

The closing date for applications is 12 noon GMT on Friday 8th February 2019.