Computational Physics

Computational Physics is a basic specialisation that offers broad opportunities for future employment in research, development, data analytics and informatics-related industry sectors. The MSc Computational Physics is developed in close connection with the more applied NanoBio and - specialties, offering you both solid training in computational methods and direct access to laboratory-based research projects.



The programme is aimed at students with a strong background in Physics or related Natural Sciences, who wish to learn how to convert a mathematical model of a physical system into accurate and robust computer programmes that can capture quantitatively its behaviour.



- At UCD, our MSc Programme in Computational Physics is developed in close connection with the more applied NanoBio and NanoTechnology specialties, offering students both a solid training in computational methods and a direct access to laboratory-based research projects.



- The programme will enhance students’ CVs with expertise which is much sought-after by employers in a broad range of sectors, including the bio-pharmaceutical, telecommunications, data mining and analysis, IT consulting and green technologies industry sectors. The course is also a stepping-stone to PhD research in the areas of theoretical and computational physics, biological and medical physics, nanotechnology and nanoscience.

Students help design their own curricula (negotiated structure)



- Students help design their own curricula (negotiated structure)



What Will I Learn?

1. Describe the state-of-the-art knowledge and skills in the field.



2. Apply knowledge gained and skills developed to a specific project in the field.



3. Use the underlying physics of the field to find, assess and use up-to-date information in order to guide progress.



4. Engage actively in addressing research topics of current relevance.



5. Set up, conduct and interpret simulations and/or experiment to create new knowledge.



6. Draw on a suite of transferrable skills including critical thinking, problem-solving, scientific report writing, communication skills, teamwork, independent work, professional networking, and project management. Presenting findings both orally and in written form, to thesis level.



7. Plan, execute and report the results of a numerical investigation and compare results critically with predictions from theory and experimental evidence.



Student Internships

There are opportunities to apply for an internship* in an academic or industry workplace. The internship comprises a research project, the theme of which is chosen by the student in agreement with the supervisor and MSc Course Director. The project may include experimental research, modelling/simulations research, and/or other research appropriate to the MSc programme theme.



*Placements are secured through a competitive process and are not guaranteed.

Stage 1 Core Modules

PHYC41090 Bio-inspired Technologies PHYC Autumn 5



Stage 1 Options - A) Min 0 of:

Optional modules suggested - final approval of module choices following consultation with Programme Director.

COMP30030 Introduction to Artificial Intelligence Autumn 5

COMP30250 Parallel Computing Autumn 5

PHYC40400 Nanooptics and biophotonics Autumn 5

PHYC40410 Physics of nanomaterials Autumn 5

PHYC40470 Computational Biophysics and Nanoscale Simulations Autumn 5

PHYC40930 Ultrafast Soft X-ray Photonics Autumn 5

PHYC40940 Bio-inspired technologies Autumn 5

PHYC41070 Techniques in Biophysics Autumn 5

STAT30010 Time Series Autumn 5

STAT40400 Monte Carlo Inference Autumn 5

STAT40800 Data Prog with Python (online) Autumn 5

IA40430 Creative Thinking & Innovation Autumn&Spring&Summer(separate) 5

ACM30020 Applied Analysis Spring 5

COMP40400 Bioinformatics Spring 5

COMP47590 Advanced Machine Learning Spring 5

PHYC40210 Applied Optics Spring 5

PHYC40430 Nanomechanics - from single molecules to single cells Spring 5

PHYC40650 Advanced Statistical Physics Spring 5



Stage 1 Options - B)1 of:

Students must take one of the following modules:

PHYC40850 Physics Research Project 45 2 Trimester duration (Spr-Sum) 45

PHYC40860 Physics Research Project 60 2 Trimester duration (Spr-Sum) 60

PHYC40840 Physics Research Project 30 Summer 30

This programme is intended for applicants who have a strong background in physics, chemistry, engineering, material sciences or a related discipline with a significant physics content. An upper second class honours or international equivalent is required. In special circumstances, students with a strong physics background and 2.2 class honours may be accepted.



Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.



Students meeting the programme’s academic entry requirements but not the English language requirements, may enter the programme upon successful completion of UCD’s Pre-Sessional or International Pre-Master’s Pathway programmes. Please see the following link for further information http://www.ucd.ie/alc/programmes/pathways/



These are the minimum entry requirements – additional criteria may be requested for some programmes



You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage. https://tinyurl.com/2ae2ffax

1 year full-time. Delivery: On Campus.

Next Intake: September 2025.

Career & Graduate Study Opportunities

The programme prepares you for a career in industry or for further PhD research. Career opportunities are broad, including the bio-pharmaceutical, telecommunications, data mining and analysis, IT consulting and green technologies industry sectors, both in Ireland and internationally. It is also a stepping stone to PhD research in the areas of theoretical and computational physics, biological and medical physics, nanotechnology and nanoscience. Recent and prospective employers include Deloitte, Murex Inc., Intel, Pfizer, MSD, Philips, Tullow Oil, the University of Edinburgh, Imperial College London, and the National Institutes of Health, USA.