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 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. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.