Specialised MSc Degrees

NFQ Level 9, Major Award

The MSc may be taken full-time over 12 months or part-time over 24 months from the date of first registration for the programme. It consists of (i) lectures, (ii) laboratory work on set experiments and (iii) a dissertation based on individual research and development in the selected field of modern analytical science, under the supervision of an expert staff member. Candidates may need to secure appropriate day release from industry. Part of the lecture course will also be available through online blended e-learning.

Programme Requirements
The MSc Degree is awarded to successful candidates after passing written examinations across all taught modules, including the continuously assessed practical module CM6015, and the research project (from CM6020-22), which has to be written up in the form of a dissertation and approved by the external examiner.

Students take 90 credits as follows:

Part I
CM6012 Modern Analytical Techniques, Chemical Data Analysis and GLP (10 credits)
CM6013 Separation Science, Sensors and Process Analytical Technology (10 credits)
CM6014 Materials, Pharmaceutical and Bio-analysis (10 credits)
CM6015 Practice of Analytical Chemistry (10 credits)
CM6026 Industry Led Workshops (5 credits)
CM6027 Taught Postgraduate Transferable Skills Development (5 credits)

Plus 10 credits from the following areas of application:
EV4002 Environmental Monitoring (10 credits)
or
PF6301 Biopharmaceuticals: Formulation, Secondary Processing and Regulation (10 credits)

Part II
Plus ONE of the following Research Projects:
CM6020 Research Project and Dissertation in Analytical Chemistry (30 credits)
CM6021 Research Project and Dissertation in Environmental Analytical Chemistry (30 credits)
CM6022 Research Project and Dissertation in Pharmaceutical Analysis (30 credits)

NOTE: The choice of Research Project informs the choice of MSc programme.

Analysis of Pharmaceutical Compounds
Module Semester Information may be found here. Module Descriptions may be found here.
Analytical Chemistry
Module Semester Information may be found here. Module Descriptions may be found here.
Environmental Analytical Chemistry
Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2022/2023 Book and for each module in the Book of Modules, 2022/2023.

Programme Learning Outcomes for MSc (Analysis of Pharmaceutical Compounds) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve problems in the analysis of pharmaceutical compounds;
• Outline fundamental and applied aspects of pharmaceutical analysis;
• Design and carry out a method of pharmaceutical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and pharmaceutical communities;
• Carry out research and method development in pharmaceutical analysis;
• Prepare a written research report in the form of a dissertation.

Programme Learning Outcomes for MSc (Analytical Chemistry) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve analytical chemistry problems;
• Outline fundamental and applied aspects of analytical chemistry;
• Design and carry out a method of chemical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and analytical science communities;
• Carry out research and method development in analytical science;
• Prepare a written research report in the form of a dissertation.

Programme Learning Outcomes for MSc (Environmental Analytical Chemistry) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve environmental analytical chemistry problems;
• Outline fundamental and applied aspects of environmental analytical chemistry;
• Design and carry out a method of environmental chemical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and environmental science communities;
• Carry out research and method development in environmental analytical science;
• Prepare a written research report in the form of a dissertation.

The MSc (Biotechnology) is a full-time intensive course running for 12 months from the date of first registration for the programme.

Programme Requirements
The programme will consist of lectures, tutorials, and set practical sessions, with the emphasis on training in modern techniques of biotechnology. The MSc Degree (Biotechnology) is awarded to successful candidates after passing written examinations across all eight taught modules, the continuous assessment of practical work and a six-month research project (BT6002), which has to be written up in the form of a dissertation and approved by the external examiner.

Students take 90 credits as follows:

BC6001 Cell and Molecular Biology (5 credits)
BT6001 Genetic Engineering (5 credits)
CM6011 Modern Methods in Analytical Chemistry (5 credits)
MB6003 Functional Foods for Health (5 credits)
MB6004 Advanced Molecular Microbial Biotechnology (5 credits)
PF6301 Biopharmaceuticals: Formulation, Secondary Processing and Regulation (10 credits)
PS6001 Plant Genetic Engineering (5 credits)
either PE6008 Bioprocess Engineering (10 credits)* or
BT6003 Advanced Case Studies in Biotechnology (10 credits)*
BT6002 Dissertation in Biotechnology* (40 credits)

*Students opting to complete BT6002 in a research setting can select either PE6008 or BT6003 in consultation with the course Director. Students opting to complete BT6002 in an industrial setting must complete PE6008. In the case of a student who has previously passed the content covered in PE6008 the student will complete BT6003 subject to the agreement of the course Director.

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2022/2023 Book and for each module in the Book of Modules, 2022/2023.

Postgraduate Certificate in Biotechnology
Students who attain a pass (40%) across the taught modules, but do not reach the 50% threshold required to progress to the research dissertation will be conferred with a Postgraduate Certificate in Biotechnology. Similarly, students who pass the taught modules and do not wish to complete the research dissertation may opt to be conferred with a Postgraduate Certificate in Biotechnology.

Programme Learning Outcomes for MSc (Biotechnology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Discuss the theory and practice of bio analytical Chemistry;
• Review Molecular Biotechnology, Eukaryotic-, Prokaryotic- and Plant-Biotechnologies, recombinant DNA technologies and their application in the Biotechnology and Biopharmaceutical Industries;
• Apply fundamentals in Process and Biochemical Engineering to the Biotechnology sector;
• Outline the role of Process Validation and Quality Assurance in pharmaceutical industry;
• Discuss the latest trends in good manufacturing, laboratory and validation practices;
• Assess the principles of Food and Industrial Microbiology;
• Complete a body of independent research in a biotechnology-related area and present research findings in a minor dissertation.

Programme Learning Outcomes for Postgraduate Certificate in Biotechnology (NFQ Level 9, Minor Award)
On successful completion of this programme, students should be able to:

• Discuss the theory and practice of bio analytical Chemistry;
• Review Molecular Biotechnology, Eukaryotic-, Prokaryotic- and Plant-Biotechnologies, recombinant DNA technologies and their application in the Biotechnology and Biopharmaceutical Industries;
• Apply fundamentals in Process and Biochemical Engineering to the Biotechnology sector;
• Outline the role of Process Validation and Quality Assurance in pharmaceutical industry;
• Discuss the latest trends in good manufacturing, laboratory and validation practices;
• Assess the principles of Food and Industrial Microbiology.

The MSc (Bioinformatics and Computational Biology) may be taken full-time over 12 months or part-time over 24 months from the date of first registration for the programme. The MSc programme has four different streams: for Biology, Mathematics, Statistics and Computer Science graduates, respectively [for graduates of cognate disciplines, the assignment to a particular stream will be decided by the Programme Director].

Programme Requirements
Part-time students take between five and seven of their twelve taught modules in each academic year and undertake the project in the second academic year. The modules to be taken by the part-time students in each of their two academic years are specified by the course director.

Note: Students cannot choose a module already completed (for example, as part of their undergraduate degree), or with largely overlapping content to a module already completed. Evidence for this would be the production of a transcript showing all modules taken in their previous degree programme(s). The Programme Director will then assist with selecting a suitable replacement module.

Stream for Biological Science Graduates
Students take 90 credits as follows:

Core Modules
AM6016 Dynamic Machine Learning with Applications (5 credits)
AM6020 Open Source Infrastructure for Modelling and Big Data (5 credits)
CS6405 Datamining (5 credits)
CS6501 Programming for Bioscientists I (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6302 Computational Microbiome Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
ST3300 Data Analysis I (5 credits)
ST4400 Data Analysis II (5 credits)
ST5005 Introduction to Probability and Statistics (5 credits)

Elective Modules
Students choose one module from:
MS6005 Discrete Mathematics (5 credits)
CS6503 Introduction to Relational Databases (5 credits)

Stream for Computer Science Graduates
Students take 90 credits as follows:

Core Modules
ST5005 Introduction to Probability and Statistics (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
CS6405 Datamining (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6302 Computational Microbiome Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
ST3300 Data Analysis I (5 credits)
ST4400 Data Analysis II (5 credits)

Elective Modules
Students choose one module from:
MS6005 Discrete Mathematics (5 credits)
CS6501 Programming for Bioscientists I (5 credits)

Stream for Mathematics Graduates
Students take 90 credits as follows:

Core Modules
Choice of ST3300 Data Analysis I (5 credits)
or ST4400 Data Analysis II (5 credits)
AM6016 Dynamic Machine Learning with Applications (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
AM6020 Open Source Infrastructure for Modelling and Big Data (5 credits)
CS6405 Datamining (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6302 Computational Microbiome Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)

Elective Modules
Students choose one module from:
CS6503 Introduction to Relational Databases (5 credits)
CS6501 Programming for Bioscientists I (5 credits)

Stream for Statistics Graduates
Students take 90 credits as follows:

Core Modules
AM6016 Dynamic Machine Learning with Applications (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
AM6020 Open Source Infrastructure for Modelling and Big Data (5 credits)
CS6405 Datamining (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6302 Computational Microbiome Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
MS6005 Discrete Mathematics (5 credits)

Elective Modules
Students choose one module from:
CS6503 Introduction to Relational Databases (5 credits)
CS6501 Programming for Bioscientists I (5 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2022/2023 Book and for each module in the Book of Modules, 2022/2023.

Postgraduate Diploma in Bioinformatics and Computational Biology
Students who do not reach the average mark of 50% threshold required to progress to the research dissertation will be conferred with a Postgraduate Diploma in Bioinformatics and Computational Biology. Similarly, students who pass the taught modules and do not wish to complete the research dissertation, may opt to be conferred with a Postgraduate Diploma in Bioinformatics and Computational Biology.

Programme Learning Outcomes for MSc (Bioinformatics and Computational Biology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Have a solid background in the theory behind bioinformatics methods and tools so that they can critically evaluate research in bioinformatics;
• Use existing bioinformatics methods and tools and rapidly learn to apply new methods and tools;
• Organise and analyse large data sets generated by genomics and systems biology approaches;
• Understand the role of modelling and simulation of biological systems;
• Have a deep knowledge of the aspect of bioinformatics in which they carried out their three-month research project. This experience will prepare them for a future research career in the bioinformatics field.

The MSc in Marine Biology is a full-time multidisciplinary degree running for 12 months from the date of first registration for the programme.

Programme Requirements
This programme will consist of Part I and Part II. Part I will consist of eight taught modules to the value of 60 credits involving lectures, practicals, seminars and fieldwork. Part II will be a substantial Research Dissertation (BL6017) to the value of 30 credits for those meeting progression requirements of Part I of the programme. Each of the prescribed taught modules will be examined by a written paper and/or continuous assessment. Each candidate progressing to Part II of the programme must submit the Research Dissertation (BL6017) in an area of Marine Biology by a date in August of the registration year as prescribed by the School of BEES.

Students take 90 credits as follows:

Part I
BL6012 Marine Megafauna (10 credits)
BL6013 Marine Fisheries and Aquaculture (10 credits)
BL6014 Marine Fieldwork and Survey Techniques (10 credits)
BL6015 Practical Marine Workplace Skills (5 credits)
BL6016 Marine Ecology and Conservation (10 credits)
BL6019 Ecological Applications of Geographical Information Systems (5 credits)
BL6020 Genetics and the Marine Environment (5 credits)
BL6026 Introductory Quantitative Skills for Biologists using R (5 credits)

Part II
BL6017 Dissertation in Marine Biology (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2022/2023 Book and for each module in the Book of Modules, 2022/2023.

Postgraduate Diploma in Marine Biology
Students who achieve 40% in each individual taught module in Part I but fail to achieve the requisite grade of 50% across the taught modules, or students who pass Part I and do not wish to complete the Research Dissertation (Part II) may opt to be conferred with a Postgraduate Diploma in Marine Biology.

Programme Learning Outcomes for MSc (Marine Biology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Recall marine flora and fauna, the marine environment and its biological and physical properties and processes;
• Assess the sustainability of exploitation (fisheries and aquaculture) and assess the impact of other anthropogenic factors on the marine environment;
• Define the roles of management and conservation across the marine environment;
• Demonstrate a wide range of research skills (field and laboratory) including safety related and professional qualifications;
• Undertake independent research in the field of Marine Biology;
• Apply the skills acquired in this course in the working environment enabling the development of policy.

Programme Learning Outcomes for Postgraduate Diploma in Marine Biology (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Recall marine flora and fauna, the marine environment and its biological and physical properties and processes;
• Assess the sustainability of exploitation (fisheries and aquaculture) and assess the impact of other anthropogenic factors on the marine environment;
• Define the roles of management and conservation across the marine environment;
• Demonstrate a wide range of research skills (field and laboratory) including safety related and professional qualifications;
• Apply the skills acquired in this course in the working environment enabling the development of policy.

The MSc in Mathematical Modelling and Machine Learning is a full-time, blended learning programme running for 12 months from the date of first registration for the programme.

Programme Requirements

Students take 90 credits as follows:

Part I
AM6004 Numerical Methods and Applications (5 credits)
AM6005 Nonlinear Dynamics (5 credits)
AM6007 Scientific Computing with Numerical Examples (10 credits)
AM6015 Computational Techniques with Networks (5 credits)
AM6016 Dynamic Machine Learning with Applications (5 credits)
AM6017 Complex and Neural Networks (5 credits)
AM6020 Open Source Infrastructure for Mathematical Modelling and Big Data Applications (5 credits)
CS6421 Deep Learning (5 credits)
EE6024 Engineering Machine Learning Solutions (5 credits)
ST4060 Statistical Methods for Machine Learning I (5 credits)
ST4061 Statistical Methods for Machine Learning II (5 credits)

Students who have taken any of the above modules in a previous degree must select alternative modules (subject to availability and timetabling) in consultation with the Programme Coordinator.

Part II
AM6021 Dissertation in Mathematical Modelling and Machine Learning (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2022/2023 Book and for each module in the Book of Modules, 2022/2023.

Postgraduate Diploma in Mathematical Modelling and Machine Learning
Students who pass Part I but who fail to achieve a minimum aggregate of at least 50% across all modules in Part I at the first attempt, or who choose not to progress to Part II and exit the programme, will be conferred with the Postgraduate Diploma in Mathematical Modelling and Machine Learning.

Programme Learning Outcomes for MSc (Mathematical Modelling and Machine Learning) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Apply the basic concepts, theories, principles and practical methods of mathematical modelling and machine learning to analyse and solve theoretical and practical problems;
• Give clear and organized written and verbal explanations of ideas in the areas of mathematical modelling and machine learning;
• Critically discuss and evaluate the concepts and examples in several areas of mathematical modelling and machine learning;
• Extend the given course material to solve original problems and develop associated computer codes;
• Contribute effectively as members of project teams dealing with mathematical models and their computer implementation, including the delivery of oral presentations and written reports.

Programme Learning Outcomes for Postgraduate Diploma in Mathematical Modelling and Machine Learning (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Apply the basic concepts, theories, principles and practical methods of mathematical modelling and machine learning to analyse and solve theoretical and practical problems;
• Give clear and organized written and verbal explanations of ideas in the areas of mathematical modelling and machine learning;
• Critically discuss and evaluate the concepts and examples in several areas of mathematical modelling and machine learning;
• Use the given course materials and computer code to solve problems;
• Contribute effectively as members of project teams dealing with mathematical models and their computer implementation, including the delivery of oral presentations and written reports.