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. This course combines teaching in data analytics, AI and machine learning (ML), systems biology, precision medicine, health informatics and connected health.

Modules on offer cover the following major themes of data analysis in biomedicine including:

  • State-of-the-art methods in AI/Machine Learning and their applications to biological and medical data
  • Programming and tools for AI
  • Tools and methods for large scale data analytics
  • Data visualisation
  • Nature and structure of biological and medical data including those produced by omics and imaging methods
  • Design of biological and medical research projects
  • Ethical and privacy issues associated with the use of medical and biological data and analysis results

This course is eligible for UCD Global Excellence Scholarships. For more information on these scholarships and application details visit this link.  

Click this link and follow the steps outlined

Applications are currently open for the 2024-25 September intake and can be made via the UCD applications page

The programme is aimed at computer scientists, data scientists, mathematicians, and statisticians. We also offer the course for biologists who have good computer skills. Entry requirements are a Bachelor’s degree (minimum 2H1), good programming skills and a solid foundation in statistics/mathematics or biology.

View All Modules Here >>

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.

The programme is delivered by traditional face to face lectures, tutorials, 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.

The programme is aimed at computer scientists, data scientists, mathematicians and statisticians. We also offer the course for biologists who have good computer skills.

Entry requirements are a Bachelor’s degree (min 2H1), good programming skills, and a solid foundation in statistics/mathematics or biology.

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 (see code X903 full-time or X984 part-time).

 

  • The School welcomes applications from eligible international applicants.
  • Click this link and follow the steps outlined to apply
  • For more information on studying at UCD as an international student please click here.

This course is eligible for UCD Global Excellence Scholarships. For more information on these scholarships and application details visit this link.  

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

Programme Director Programme Administrator

Dr Vadim Zhernovkov
Systems Biology Ireland
UCD School of Medicine
University College Dublin, Belfield

Email: vadim.zhernovkov@ucd.ie

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

Postgraduate Medicine Administrator
Health Sciences Centre
UCD School of Medicine
University College Dublin, Belfield


Email: postgraduate.medicine@ucd.ie

Key Information:

  • CAO Code X903 / X984
  • Duration 12 months (FT) / 2 years (PT)
  • Schedule Full-Time / Part-Time

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