The programme is aimed at:
Computer scientists, data scientists, and statisticians. Applicants are expected to have programming experience and a strong background in mathematics, including calculus, linear algebra, and probability.
Biologists and clinicians. Applicants are expected to have good programming skills and experience in data analysis or bioinformatics.
The entry requirement is an honours bachelor's degree (minimum 2H1) or its international equivalent. Applicants with a 2H2 honours bachelor's degree may also be considered if they have relevant industry or academic experience in data science applications, machine learning, deep learning, drug development, bioinformatics, or computer vision.
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.
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 GDP This programme equips students with the fundamental skills to work in a variety of roles in the biopharmaceutical industry, healthcare sector or biomedical research including AI/ML engineer, data scientist, bioinformatics specialist. In addition, this course will enhance the academic profile and practical skills of students, making them highly competitive for PhD programmes in universities and research departments in biopharmaceutical companies. Recent career destinations of our graduates include Novartis, Optum and other employers. Multiple graduates continued their education in PhD programmes and are now part of UCD, other Irish or international universities, including the Icahn School of Medicine at Mount Sinai and Harvard Medical School in the USA. Students are offered the opportunity to undertake an internship module* as part of the programme. The aim of this module is to provide hands-on experience in data analysis using real-life problem-solving projects in collaboration with our academic, clinical and industry partners. The placement has limited capacity and entry is competitive. Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information. Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Mos