Comparative Social Change
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.
| Award Name | Degree - Masters (Level 9 NFQ) |
|---|---|
| NFQ Classification | Major |
| Awarding Body | National University of Ireland |
| NFQ Level | Level 9 NFQ |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
|---|---|---|---|
| Degree - Masters (Level 9 NFQ) | Major | National University of Ireland | Level 9 NFQ |
Duration
1 year full-time.
MODE OF DELIVERY: Face-to-Face
Entry Requirements
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
Careers / Further progression
Careers & Employability
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.
Further information
Next Intake: 2024/2025 September.
MSc Computational Physics (F120) Full Time
EU fee per year - € 10200
nonEU fee per year - € 29100
MSc Computational Physics (F121) Part Time
EU fee per year - € 5030
nonEU fee per year - € 14550
***Fees are subject to change
The following entry routes are available:
MSc Computational Physics (Negotiated Learning) FT (F120)
Duration 1 Years Attend Full Time
Deadline Rolling*
* Courses will remain open until such time as all places have been filled, therefore early application is advised
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 NanoTechnology 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 will learn how to plan and develop their modelling programs and algorithms to imitate the underlying processes of a physical system, and how to analyse and test the results of their calculations. In the negotiated learning framework, the students will be able to take modules in programming, mathematical and numerical methods and deepen their knowledge in modern theoretical and experimental physics research projects from atomistic and molecular modelling to nanooptics, spectroscopy and nanotechnology related applications.
Students will learn how to plan and develop their modelling programs and algorithms to imitate the underlying processes of a physical system, and how to analyse and test the results of their calculations. In the negotiated learning framework, the students will be able to take modules in programming, mathematical and numerical methods and deepen their knowledge in modern theoretical and experimental physics research projects from atomistic and molecular modelling to nanooptics, spectroscopy and nanotechnology related applications.
Modules will be decided upon agreement with the Programme Director, indicative modules available include:
Applied Quantum Mechanics
Computational Biophysics and Nanoscale Simulations
Nanofluidics and Biosimulation
Biomimicry
Numerical Weather Prediction
Advanced Statistical Physics
Advanced Quantum Mechanics
Numerical Algorithms
Stochastic Models
Time Series Analysis
Physics Research Project
Apply knowledge gained and skills developed to a specific project in the field.
Describe the state-of-the art knowledge and skills in the field.
Draw on a suite of transferrable skills including critical thinking, problem solving, scientific report writing, communication skills, team-work, independent work, professional networking, project management. Presenting findings both orally and in written form, to thesis level.
Engage actively in addressing research topics of current relevance.
Plan, execute and report the results of a numerical investigation and compare results critically with predictions from theory and experimental evidence.
Set up, conduct and interpret simulations and/or experiment to create new knowledge.
Use the underlying physics of the field to find, assess and use up-to-date information in order to guide progress.
Nicolae Buchete
+353 (0)1 716 2088