A unique studentship opportunity to join an interdisciplinary team with world class reputation is offered by Newcastle University. This PhD studentship is part of a biomedical research European project funded by FOREUM (Foundation for Research in Rheumatology) and with partners in Italy, Spain and the UK. The project focuses on Rheumatoid Arthritis (RA), affecting 35 million people worldwide with many of them unable to achieve sustained disease remission with current treatments. The aim of the project is to understand and characterise the disease mechanisms at molecular level that lead to disease flares, with a combination of skills including experimental medicine, immunology and artificial intelligence. In this doctoral project you will focus on the challenge of devising innovative strategies to process, using artificial intelligence, the rich data that the project will generate in order to design prediction models relevant to RA flares (e.g.

This is a unique opportunity to secure a fully funded 4-yr PhD position in a world-class university, with dual academic support being provided by the Department of Applied Mathematics and Theoretical Physics (Professor Carola-Bibiane Schönlieb; http://www.damtp.cam.ac.uk/) and the Department of Haematology (Professor Willem H Ouwehand; http://www.haem.cam.ac.uk/). During your PhD you will work on large genomics data sets drawn from the UK-wide genome resources and new data currently being generated by the international Blood transfusion Genomics Consortium (www.bgc.io), This is your opportunity in putting your mind to some of the major challenges in healthcare-focused machine learning and AI and genomics and to make a key contribution in bringing genomics to the frontline of medicine. The Cambridge University Departments of Applied Mathematics and Theoretical Physics and Haematology work with colleagues at University College London and its hospital UCLH in applying a cross-disciplinary approach to develop healthcare-focused machine learning and AI solutions of the future (https://www.youtube.com/watch?v BIyTgiF6wCw). This is a challenge that requires critically-minded thinkers.

Thanks to AHRC Collaborative Doctoral Partnership funding held jointly by Historic Environment Scotland (HES) and the University of Glasgow, we are offering a 45 month (3.75 years) PhD scholarship on developing approaches to integrate automation-led detection routines into workflows used in the professional practice of archaeological prospection and landscape archaeology, notably for large scale heritage management. The supervisors will be Dr Rachel Opitz (Archaeology) and Dr Jan Paul Siebert (Computer Science) at University of Glasgow, and Dr Lukasz Banaszek and Mr David Cowley (HES). Automated detection routines have been viewed as potentially useful or even transformative for several decades, and recent progress in artificial intelligence (AI) based in machine learning and computer vision has moved these approaches from potentially interesting to practically implementable across a variety of applications. Within archaeology, the potential of AI-led approaches and heavily automated image processing for partially automating the identification of archaeological features and landscape changes has been demonstrated in several studies. Their implementation has brought measurable benefits, leading to increased investment in their development. While the technologies themselves are being pursued, less attention has been paid to the analytical and interpretive frameworks within which semi-automated computational approaches to feature identification, notably AIs, are integrated into practices of archaeological landscape interpretation, particularly within heritage management bodies.

Defining the roadmaps for Artificial Intelligence applications for railway operations and network management Applications are invited for a PhD studentship in innovative approaches in artificial intelligence for railway scheduling and operations, to be based in Institute for Transport Studies at University of Leeds. The position is an opportunity to combine cutting-edge research at the intersection of railway scheduling and artificial intelligence techniques such as machine learning, neural networks. The overall objective of the PhD research project is to investigate the potential of Artificial Intelligence (AI) in the rail sector and contribute to the definition of roadmaps for future research in operational intelligence and network management. In particular, the student will develop and compare different AI approaches, e.g. machine learning, deep and reinforcement learning, for railway traffic planning and management. He or she will have a chance to investigate using AI for solving combinatorial optimization problems, AI for supporting optimization models, with special focus on the optimization models for railway operations and management.

We are on the lookout for the best and brightest students interested in the intersection of music/audio technology and AI. For this round of applications we are offering a number of scholarships to applicants who are ordinarily resident in the UK (i.e. have lived and studied/worked in the UK at least the last three years – this includes EU nationals) and a smaller number of scholarships to international students. We have a large number of 4-year PhD studentships available for home, EU and international students starting in September 2020 which will cover the cost of tuition fees and will provide an annual tax-free stipend (£17,009 in 2019/20). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events. Please see the international PhD scholarships page for full details of Queen Mary's international funding partners, including other schemes not listed here.

The UKRI Centre for Doctoral Training (CDT) in the'Application of Artificial Intelligence to the study of Environmental Risks' (AI4ER) will, through several multi-disciplinary cohorts, train researchers uniquely equipped to develop and apply leading edge computational approaches to address critical global environmental challenges by exploiting vast, diverse and often currently untapped environmental data sets. Embedded in the outstanding research environments of the University of Cambridge and the British Antarctic Survey (BAS), the AI4ER CDT will address problems that are relevant to building resilience to environmental hazards and managing environmental change. The primary application areas will be: a) Weather, Climate and Air Quality, b) Natural Hazards, c) Natural Resources (food, water & resource security and biodiversity). The AI4ER CDT is offering at least 10 fully-funded PhD studentships to start in October 2020. Students in the CDT cohorts engage in a one-year Master of Research (MRes) course with a taught component and a major research element, followed by a three-year PhD research project.

Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Electrical and Electronic Engineering Department). This studentship will form part of a newly established International Centre for Spatial Computational Learning http://spatialml.net, and a supervisory team will be allocated based on the student's interest from the Imperial College supervisors participating in the Centre. This is an exciting cutting-edge project involving close collaboration between Imperial College (UK), the University of California Los Angeles (USA), the University of Toronto (Canada), and the University of Southampton (UK). The successful candidate will be based at Imperial but will have the opportunity to travel frequently to America to attend research meetings and for a placement period at either UCLA or Toronto. Traditional deep learning has been based on the idea of large-scale linear arithmetic units, effectively computing matrix-matrix multiplication, combined with nonlinear activation functions.

We are seeking excellent candidates with interests in Artificial Intelligence (AI), machine learning and deep learning who want to study at a top 10 UK research-led University whilst working with industrial partners. This project is part of the EPSRC Centre for Doctoral Training in Embedded Intelligence. In choosing this project you'll work alongside academics that are leaders in their field and benefit from a four-year studentship award that includes an enhanced EPSRC tax-free annual stipend of at least £17,553 per annum and UK/EU tuition fees. Furthermore, you will have access to a personal training budget of £10,000, which is in addition to a research budget and support from academic members of staff and industrial partners. Loughborough University aims to ensure equality for men and women.