Chair and Lecturer/Senior Lecturer in Machine Learning
There is an exciting opportunity to join the Machine Learning group at the Department of Computer Science, University of Sheffield. Two appointments are currently advertised; we expect to make one at Chair level, and one at Lecturer/Senior Lecturer level. Please follow the links below for more information, and to apply:
Machine learning at Sheffield
Machine learning is one of the principal technologies underpinning the current revolution in data science, and the key technology for recent advances in artificial intelligence. The Sheffield Machine Learning group is at the heart of both applications in artificial intelligence and data science.
Our interactions in artificial intelligence are through the department's Natural Language Processing group, its Speech and Hearing group, as well as Sheffield Robotics, a cross-faculty centre of excellence in robotics.
Our activities in data science are primarily a collaboration with the School of Mathematics and Statistics through the Open Data Science Initiative (ODSI), a cross-faculty initiative targeted at developing new machine learning and statistical methodologies and making techniques available as widely as possible. The ODSI also runs summer schools, supports the development of new taught programs in data and through Mike Croucher (EPSRC Research Software Engineering Fellow) delivers scientific software support to facilitate the teaching of data science.
Further opportunities for collaboration are available at a range of other data-driven centres throughout the University including the Centre for Assistive Technology and Connected Healthcare (a collaboration with the School of Health and Related Research) and the Sheffield Institute for Translational Neuroscience, a centre of excellence in translational healthcare with a focus on neurodegenerative disease. The Sheffield Methods Institute, a centre of excellence in social science methodology, the Sheffield Institute for International Development, the Sheffield Bioinformatics Hub and Insigneo, the institute for in silico medicine.
We welcome applications from researchers with an international track record in the development of new machine learning methodologies both in theory and practice. Successful candidates will also be expected to play an active role in the development and delivery of our new MSc course in Data Analytics.
Related centres and institutes at the University of Sheffield
The Department of Computer Science and the School of Health and Related Research (ScHARR) collaborated to set up the Centre for Assistive Technology and Connected Healthcare (CATCH), which has now expanded to encompass researchers from 14 university departments across all 5 university faculties. The Computer Science Department is involved in all of the CATCH research themes, including Human Communication Technology, Assistive Robotics, Complex Behavioural Interventions and Intelligent Personalised Support. Machine Learning at Sheffield is particularly involved in the latter theme, aiming to transform the way healthcare is provided at home and in the community, through the collection, analysis and appropriate use of the many sources of data now available through wearable and environmental sensors, coupled with the greater availability and sharing of electronic health records. CATCH provides the opportunity for collaboration across the university and with local health and care providers, including Sheffield Teaching Hospitals, and links into the joint University of Sheffield / NHS strategic initiative known as Care 2050. For more information, see www.catch.org.uk.
Translational Bioinformatics and SITraN
The Sheffield Institute for Translational Neuroscience (SITraN) is an integrative biomedical research centre that represents and provides a powerful translational impact opportunity for computer sciences.By embracing and integrating clinical, biomedical, model organism, translational, and computational research and data, it provides an ideal environment for developing and deploying real life solutions to complex biomedical problems. Our major computational foci are machine learning in precision medicine, systems and network medicine for multi-scale network modelling to deliver causal models, drug repurposing and drug target prioritisation, and health data informatics for patient health. Part of the Sheffield Bioinformatics Hub, SITraN is the home of bioinformatics for biomedical research at the University. It’s Centre for Genome Translation partners with Harvard University, Industry, local hospitals and The UK 100 000 genomes project to perform high dimensional data integration translation deliver new therapeutic understanding in neurodegenerative diseases such as Alzheimer’s, ALS and Parkinson’s. For more information, see www.sitran.org.
The Insigneo Institute for in-silico medicine is a collaborative initiative between the University of Sheffield and Sheffield Teaching Hospitals NHS Foundation Trust. Multi-disciplinary in its structure, the Institute involves 139 academics and clinicians who collaborate to develop computer simulations of the human body and its disease processes, that can be used directly in clinical practice to improve diagnosis and treatment. In-silico medicine (also known as “computational medicine”) is the direct use of computer simulation in the diagnosis, treatment, or prevention of a disease. More specifically, in silico medicine is characterised by modelling, simulation, and visualisation of biological and medical processes in computers with the goal of simulating real biological processes in a virtual environment. This is a challenging application of computing technology in healthcare, and Sheffield has become the UK’s principal centre for this work. Insigneo performs cutting-edge research in areas of fundamental and applied biomedical modelling, imaging and informatics, and aims to bring about a transformational change in healthcare through multidisciplinary collaborations across many strategic areas, which will include personalised diagnosis and treatment and improvements in independent, active and healthy ageing. For more information, see www.insigneo.org.
The University of Sheffield and Sheffield Hallam University have come together to create Sheffield Robotics, which seeks to integrate robotics research within the City and across the wider region. Founded in 2011, Sheffield Robotics operates dedicated research facilities for robotics in both universities and has academic and research student members from many disciplines and departments. With partners such as the Advanced Manufacturing Research Centre, Sheffield Robotics covers a broad spectrum of research in robotics and autonomous systems, including industrial, field, and service robotics.
Sheffield Robotics has one of the largest portfolios of ongoing publicly-funded robotics research in the UK, supported by both the UK Research Councils and the European Union. We are also building research partnerships with leading industrial, commercial, and government organisations in order to ensure the real-world relevance and impact of our research. As a member of the Northern Robotics Network, and of the EPSRC UK-RAS Network, Sheffield Robotics acts as a central hub for robotics research within the UK. Through our international links, we seek to play a leading role in the world robotics community, and to promote the development of ethical, useful, safe, and sustainable robotic and autonomous systems that can enhance human prosperity across the globe. For more information, see www.sheffieldrobotics.ac.uk.