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Lecturer in Genomic Informatics

Centre and Wessex Secure Data Environment. The University is nationally leading in artificial intelligence techniques applied to genomic data. The candidate The appointee will be expected to develop and

Research Group Leader (Career Track) Artificial Intelligence – Fundamentals (all genders)

research together on this every day. Our team at the “Centre for Artificial Intelligence in Public Health Research” is looking forward to your application! The new “Centre for Artificial Intelligence in

Creation of a new research group

of interest include, but are not limited to: Auditory processing from the periphery to the cortex Artificial intelligence , (neuro)computational methods, and brain machine interfaces applied to auditory


innovative computational approaches (e.g., artificial intelligence and/or machine learning) to explore large datasets to gain insights into genome function. The successful candidate will train Ph.D., M.D./Ph.D

MRC AIM Doctoral Training Partnership: School of Veterinary Medicine & Science

: An artificial intelligence approach to new druggable therapeutic targets and drug discovery Supervisors: Tania Dottorini, [email protected] , Michelle Baker (UoN), Julie Morrissey (UoL), Stephan

PhD Studentship: An Artificial Intelligence Approach for Epidemiological Samples and Their Implementation in Mental Healthcare Systems

Artificial Intelligence holds tremendous potential to revolutionise decision-making in mental healthcare systems. By analysing vast amounts of patient data and identifying patterns, AI algorithms

Postdoctoral Fellow (Multiple Vacancies)

, the Postdoctoral Fellow will conduct specialized cardiovascular research techniques and procedures with focus on artificial intelligence and machine learning platforms that will promote precision medicine and

Post-doctoral Fellow in the Department of Clinical Oncology, School of Clinical Medicine

experience in one or more of the following areas: development of methods for multi-omics data integration, application of artificial intelligence models in life science, single-cell data analysis, and spatial

PhD position - methods for clinical impact assessment of (AI) prediction algorithms

, or artificial intelligence . You demonstrate a keen interest in the methodology of medical research, have expertise in working with prediction modelling techniques, have experience with programming (e.g., in R

University of Leeds logo

The aim of the CDT is to train a new generation of researchers with the expertise and knowledge to transform medical diagnosis through the application of Artificial Intelligence.

Applications and Open Day

Ukri centre for doctoral training.

Join with us in transforming cancer diagnosis and care through the application of Artificial Intelligence (AI).

We are looking for outstanding graduates from science, engineering, computing, mathematics, and health disciplines.

The Centre provides a fully funded 4-year integrated PhD and MSc.

  • You will receive a masters-level grounding in AI, health informatics and specialist areas related to your research
  • Your PhD research will be supported by supervisors who are leading researchers and innovators in the area of AI and medical diagnosis and care
  • During years 2-3 there is the opportunity for a 3-month placement with one of our industry or public-sector partners
  • Where appropriate for individual research topics, there is the opportunity for short study visits with our international partner universities
  • Work closely with health professionals and clinical research teams through our partnership with LTHT
  • Participate in an annual CDT Conference and CDT seminar series
  • Join in masterclasses organised jointly with The Alan Turing Institute on topics such as shaping policy for government, and journalistic communication
  • Gain training on developing impact from research, responsible innovation, and broad research skills
  • World-class interdisciplinary location in LIDA , the Leeds Institute for Data Analytics at the University of Leeds.

There are a number of highly competitive EPSRC Fully Funded Studentship Awards for Session 2023/24 covering the full cost of University Fees plus Maintenance. Applications are open to all applicants, with opportunities for Non-UK Fee rated applicants limited by UKRI to three. There are also a limited number of places available to Non-UK Fee rated applicants who are able to self-fund their own study or are funded by an external sponsor.

Application Deadline

Applications are now closed.

If you require any further information, please contact us at [email protected].

For more information on all our graduate programmes contact the Graduate School Office e:  [email protected]

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Artificial Intelligence Enabled Healthcare MRes + MPhil/PhD

The details for this degree are being confirmed and will be published shortly.

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Novel AI to transform healthcare

medical ai phd

Cambridge Centre for AI in Medicine

Developing novel artificial intelligence and machine learning technologies to revolutionize biomedical science, medicine and healthcare

“ AI and machine learning have the potential to truly revolutionise the delivery of healthcare, to the great benefit of patients, clinicians and the wider medical ecosystem. “

Professor  Mihaela van der Schaar , Director

“ From tackling the immediate threats of COVID-19, to the long-term transformation of healthcare systems, our network of experts is bringing next-level AI to bear on the most pressing medical issues of our time. “

Professor  Andres Floto , Co-Director


medical ai phd

The ‘Cambridge Centre for AI in Medicine’ develops pioneering AI and machine learning technologies to transform biomedical science, medicine and healthcare.

The Centre is uniquely placed at the intersection of machine learning, science and medicine. Our faculty comprises top-tier researchers from these three domains. This is not a mere juxtaposition of expertise but true interaction.

It is crucial to collaborate deeply across these disciplines because, ultimately, they fuel each other.

Tough clinical problems drive cutting-edge ML solutions. Pioneering ML solutions empower the exploration of key scientific questions. Scientific breakthroughs result in medical advances and the lives of many thousands of people are improved.

Another strength of the Centre is the close relationship to our industry partners at AstraZeneca and GSK. Their valuable input opens up the exciting opportunity to have our innovative research reaching real-world-application effectively and, in return, our collaboration informs our research with real-life demands.


medical ai phd


medical ai phd

NeurIPS 2023 Preview: Data-Centric AI for reliable and responsible AI

This is a preview of our NeurIPS Tutorial that will be presented by Mihaela van der Schaar and …

medical ai phd

Building Safe, Stable & Trustworthy AI Workshop

This is a virtual workshop scheduled for 14 November 14:00 – 15:00 GMT. The Cambridge Centre …

medical ai phd

Mihaela van der Schaar joins The Guardian’s Science Weekly podcast to tall about AI

At the start of November, Prof Mihaela van der Schaar joined Guardian science editor Ian Sample and …

medical ai phd

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Dottorato Nazionale in Intelligenza Artificiale

Logo Centro Nazionale delle Ricerche

AI & Health and Life Sciences

The application of AI in the field of health and life sciences and, in particular, the integration of AI, IoT & biorobotics foreshadows scenarios of rapid evolution towards precision medicine, an increasingly predictive, preventive, personalised and participatory medicine. The specific training pathway of this vertical component envisages the design, development and application of innovative methods, tools and systems that can be used both for basic biological and bio-engineering research, necessary for understanding the origin of pathologies and the preliminary verification of innovative solutions on computational and organ-on-chip models, and for experimental, translational and clinical medical research, in order to maximise the impact of this research on health and the quality of human life, including longevity. A pathway that starts with the generation of significant data on health status and relevant environmental conditions, moves on to their processing with AI and data science techniques for knowledge extraction and decision support, and arrives at the synthesis, implementation and monitoring of the tools and actions required for diagnostic, therapeutic and care purposes to improve the health and safety of the individual in health, social and work contexts, by means of digital tools and cyber-physical systems. Given the particular nature of the contexts affecting health, the PhD course will also address issues related to the acceptability of AI technical solutions by health professionals and patients and their effective incorporation into healthcare processes.

Lead University : Università Campus Bio-Medico di Roma

Participants Universities and Research Institutions: Consiglio Nazionale delle Ricerche, Scuola Internazionale Superiore di Studi Avanzati di Trieste, Università degli Studi di Bari “Aldo Moro”, Università degli Studi di Catania, Università degli Studi di Pavia, Università degli Studi del Piemonte Orientale, Università degli Studi di Torino, Università degli Studi di Roma Tor Vergata.

Associated Universities and Research Institutions: LUISS – Libera Università Internazionale degli Studi Sociali “Guido Carli”, Scuola Superiore Sant’Anna di Pisa, Università degli Studi della Campania “Luigi Vanvitelli”, Università degli Studi “Gabriele d’Annunzio” di Chieti-Pescara, Università degli Studi di Genova, Università degli Studi Mediterranea di Reggio Calabria, Università degli Studi di Messina, Università degli Studi del Molise, Università degli Studi della Tuscia di Viterbo, INFN – Istituto Nazionale di Fisica Nucleare, C.O.T. Cure Ortopediche Traumatologiche SpA.

Calls for admission: Calls

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medical ai phd

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Our goal is to develop AI technologies that will change the landscape of healthcare and the life sciences. This includes the whole span from the discovery of biological mechanisms to early disease diagnostics, drug discovery, care personalization and management.  Building on MIT’s pioneering history in artificial intelligence and life sciences, we are working on algorithms suitable for modeling biological and clinical data across a range of modalities including imaging, text and genomics. 

While achieving this goal, we strive to make new discoveries in machine learning, biology, chemistry and clinical sciences, and translate our discoveries into technologies that can improve people’s lives. While the Jameel Clinic focuses primarily on AI and Health, other research labs and centers affiliated with EECS have groups engaged in AI for healthcare and life sciences, including IMES , CSAIL , LIDS , and the Eric and Wendy Schmidt Center at the Broad Institute .

medical ai phd

Latest news in AI for healthcare and life sciences

Twelve with mit ties elected to the national academy of medicine for 2023.

Five MIT faculty, along with seven additional affiliates, are honored for outstanding contributions to medical research.

SMART launches research group to advance AI, automation, and the future of work

Mens, Manus and Machina (M3S) will design technology, training programs, and institutions for successful human-machine collaboration.

How machine-learning models can amplify inequities in medical diagnosis and treatment

MIT researchers investigate the causes of health care disparities among underrepresented groups.

How to help high schoolers prepare for the rise of artificial intelligence

A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.

Artificial intelligence for augmentation and productivity

The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.

Upcoming events

Doctoral thesis: integrated photonics for imaging: novel sources, architectures and applications, doctoral thesis: a simulated annealing approach to designing optimal decision trees for classification, prescriptive, and survival analysis, doctoral thesis: improving performance of consensus protocols.


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    Artificial Intelligence (AI) has the potential to transform health and healthcare systems globally, yet few individuals have the required skills and

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    Seifert, PhD, Co-Director of the Artificial Intelligence and Emerging Technologies in Medicine multidisciplinary training area. “Through access to first-class

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    Learn more about PhD in Artificial Intelligence in Medicine Program including the program highlights, fees, scholarships, events and further course

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    The Cambridge Centre for AI in Medicine develops pioneering AI and machine learning technologies to transform biomedical science, medicine and healthcare.

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    The Artificial Intelligence in Medicine (AIM) PhD track will be led by co-directors DBMI Chair Isaac “Zak” Kohane and Harvard Medical School

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  14. AI for Healthcare and Life Sciences

    77 Massachusetts Ave. Room 38-401. Cambridge, MA 02139. EECS INTERNAL RESOURCES · Admin Login