MSc Artificial Intelligence (AI) for Medicine & Medical Research

MSc in Artificial Intelligence -  560

Course Features

The programme is divided into (i) introductory modules (eight mandatory modules and seven optional modules) leading to a graduate diploma (60 ECTS); and (ii) three advanced modules leading to a Master of Science, Medicine degree (90 ECTS). 

The introductory modules aim to familiarise students with the basic concepts of biology and medicine through examples and the analysis of relevant data sets. The advanced modules will focus on AI applications and include project work.

Course Overview

This Masters programme consolidates core disciplines to address a rapidly increasing skill gap in the healthcare and biomedical research sector. AI is already revolutionising medical imaging, digital pathology, pharmaceutical research, and remote sensing and connected health. In the era of genomic medicine AI will transform the way we diagnose and treat diseases reducing the impact of the healthcare crisis in industrialised countries caused by cancer, obesity and diabetes. It combines teaching in data analytics, machine learning/AI, systems biology, precision medicine, health informatics and connected health.

Who Should Take this Course?

This programme is aimed at computer scientists, data scientists, mathematicians and statisticians.  Entry requirements are a bachelor’s degree (minimum2H2), good computing skills, basic programming skills, and a solid foundation in statistics and mathematics.

What Will I Learn?

This Masters programme consolidates core disciplines to address a rapidly increasing skill gap in the healthcare and biomedical research sector. AI is already revolutionising medical imaging, digital pathology, pharmaceutical research, and remote sensing and connected health. In the era of genomic medicine AI will transform the way we diagnose and treat diseases reducing the impact of the healthcare crisis in industrialised countries caused by cancer, obesity and diabetes. It combines teaching in data analytics, machine learning/AI, systems biology, precision medicine, health informatics and connected health.

On successful completion of the programme students will be able to:

  • Demonstrate a comprehensive knowledge and understanding of the current state-of-the-art methods in AI/ML and their possible applications to biological and medical data. 
  • Understand the research questions and possible applications in these fields that can be solved using AI/ML.
  • Understand the nature and structure of biological and medical data including those produced by omics and imaging methods.
  • Understand the design of biological and medical research projects.
  • Understand how to use medical and health information systems.
  • Demonstrate a knowledge and understanding of the ethical and privacy issues associated with the use of medical and biological data and analysis results.
  • Apply AI/ML applications that can drive the discovery and development of new and highly innovative biomedical and biotech methods and products. 
  • Demonstrate skills in problem-solving and incorporating critical thinking and decision-making into a variety of clinical, biopharmaceutical, and biological research applications and environments.
  • Demonstrate the analytical and technical skills required for the analysis and interpretation of different data types in the exploitation of scientific discovery and development in industrial, academic and clinical settings.
  • Work with data from biological and biomedical databases and e-health information systems.
  • Incorporate ethical and data governance considerations into the analysis of patient and research data that satisfy concurrent data protection frameworks in the era of GDPR.

How and Where will I Learn?

The programme is delivered by traditional face to face lectures, tutorials, and lab-based sessions, together with online, synchronous and asynchronous.  Teaching. Modes of delivery will vary across modules and face to face attendance, on campus, will be required on a regular basis.

A range of assessment strategies including, written assignments, practical assessments, written examinations, reports, and research projects will be employed across the modules.

Am I Eligible for This Course?

The programme is aimed at computer scientists, data scientists, mathematicians and statisticians. 

Entry requirements are a Bachelor’s degree (min 2H2), good computing skills, basic programming skills, and a solid foundation in statistics and mathematics.

If English is not the applicant’s native language, unless the primary degree was read through English medium in an English-speaking country, an English language qualification is required. English language qualifications include a minimum score of 6.5, overall, in the International English Language Testing System (IELTS). Other evidence of proficiency in English may be accepted such as the Cambridge Certificate, TOEFL or Pearson’s Test of English, as per the standard UCD requirements

The programme major is open through the UCD online applications system www.ucd.ie/apply

International Applicants

  • The School welcomes applications from eligible international applicants.
  • For more information on studying at UCD as an international student please click here.

Indicative Course Fees

As programmes fees are subject to change, please consult the Fees & Grants Office website for the relevant fee.

Contact Us

Programme DirectorProgramme Administrator

Professor Walter Kolch
Systems Biology Ireland & Conway Institute
University College Dublin, Ireland
Phone 00353-1-716 6303
Email: walter.kolch@ucd.ie

http://www.ucd.ie/sbi/ http://www.ucd.ie/conway/

Postgraduate Medicine Administrator
Health Sciences Centre
UCD School of Medicine
University College Dublin, Belfield
Email:    postgraduate.medicine@ucd.ie