NUS Bulletin AY2020/21

The Master of Science in Applied Physics is a coursework programme initiated as a part-time programme in July 2002.  It can be enrolled on a full-time basis now.

Programme Structure

A candidate in the MSc Programme in Applied Physics by coursework must complete the following in order to be awarded the MSc degree:

Track 1: 40 modular-credit programme (for applicants who have an Honours degree or equivalent qualifications)

EITHER

1. Read and pass four PC level 5000 modules (excluding PC5198) amounting to 16 MCs. Subject to approval, students are allowed to choose not more than 12 MCs from Level 5000 modules offered by other Departments.
2. Read and pass two PC level 4000 modules amounting to 8 MCs
3. Complete a research project PC5289 equivalent to 16 MCs
4. Obtain a minimum Cumulative Average Point (CAP) of 3.00

OR

1. Read and pass seven PC level 5000 modules (excluding PC5198) amounting to 28 MCs. Subject to approval, students are allowed to choose not more than 12 MCs from Level 5000 modules offered by other Departments.
2. Read and pass three PC level 4000 modules amounting to 12 MCs.
3. Obtain a minimum Cumulative Average Point (CAP) of 3.00

Track 2: 80 modular-credit programme (for applicants who have a Bachelor’s pass degree or completed a three-year study in Physics or related discipline)

EITHER

1. Read and pass five PC level 5000 modules (excluding PC5198) amounting to 20 MCs. Subject to approval, students are allowed to choose not more than 12 MCs from Level 5000 modules offered by other Departments.
2. Read and pass six PC level 4000 modules amounting to 24 MCs
3. Read and pass one PC level 4000 module or PC level 5000 module amounting to 4 MCs
4. Read and pass four PC level 3000 modules amounting to 16 MCs
5. Complete a research project PC5289 equivalent to 16 MCs
6. Obtain a minimum Cumulative Average Point (CAP) of 3.00

OR

1. Read and pass six PC level 5000 modules (excluding PC5198) amounting to 24 MCs. Subject to approval, students are allowed to choose not more than 12 MCs from Level 5000 modules offered by other Departments.
2. Read and pass eight PC level 4000 modules amounting to 32 MCs
3. Read and pass two PC level 4000 modules or PC level 5000 modules amounting to 8 MCs
4. Read and pass four PC level 3000 modules amounting to 16 MCs
5. Obtain a minimum Cumulative Average Point (CAP) of 3.00

For admission and further details, please visit:

https://www.science.nus.edu.sg/admissions/graduates/coursework-programmes/application-information/

This programme is designed for Chemistry graduates with a 4-year Honours degree who would like to pursue a postgraduate degree in Chemistry. This programme lays the scientific foundation in chemistry for attendees for senior positions in the chemistry industry as well as to qualify for other advanced degree programmes such as PhD in Chemistry.

At the end of the programme, the student will be equipped with advanced knowledge and skills pertaining to recent developments in the Chemical Science which will enable him/her to perform with confidence leading roles as scientists, managers and entrepreneurs in Chemistry R&D and related industries.

Track 1 (40 MC Programme)

Programme Structure

The minimum candidature requirement is 2 semesters (for full-time candidature) and 4 semesters (for part-time candidature).

Students have to fulfill one of the following conditions:

Option 1 :

1. Read and pass essential module CM5198 amounting to 4 MCs
2. Read and pass five Chemistry level 5000 modules amounting to 20 MCs
3. Complete an advanced M.Sc. project module CM5100A equivalent to 16 MCs
4. Obtain a minimum Cumulative Average Point (CAP) of 3.00

Option 2 :

1. Read and pass essential module CM5198 amounting to 4 MCs
2. Read and pass five Chemistry level 5000 modules amounting to 20 MCs
3. Read and pass two Chemistry / other Major level 5000 modules amounting to 8 MCs
4. Complete a M.Sc. project module CM5100 equivalent to 8 MCs
5. Obtain a minimum Cumulative Average Point (CAP) of 3.00

Track 2 (80 MC Programme)

Programme Structure

The minimum candidature requirement is 4 semesters (for full-time candidature).

Students have to fulfill the following conditions:

1. Read and pass two Chemistry level 3000 modules amounting to 8 MCs
2. Read and pass four Chemistry level 4000 modules amounting to 16 MCs
3. Read and pass five Chemistry level 5000 modules amounting to 20 MCs
4. Read and pass essential module CM5198 amounting to 4 MCs
5. Complete a Chemistry Honours Project module CM4199A equivalent to 16 MCs
6. Complete an advanced M.Sc. project module CM5100A equivalent to 16 MCs
7. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

 For admission and further details, please visit:

https://chemistry.nus.edu.sg/education/graduate/m-sc-programme-in-chemistry-by-coursework/

This programme provides students with a good broad knowledge of the latest energy and environmental technologies, including some background in regulatory policies and risk assessments. Students will gain a deep understanding in modern materials design and synthesis strategies, advance characterization and analytical techniques, and the study of chemical structures and materials properties. They will be trained hands-on also in practical R&D skills in synthesis and characterization, fabrication and performance testing, information and literature retrieval, as well as critical interpretation and analysis.

Programme Structure

Complete 2 full-time or 4 part-time semesters of course requirements.

Students have to fulfil the following conditions:

1. Read and pass the three essential modules : CM5101, CM5151, CM5152 amounting to 12 MCs
2. Read and pass three Chemistry level 5000 modules amounting to 12 MCs
3. Complete a research & development project CM5199 equivalent to 16 MCs
4. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

For admission and further details, please visit:

https://chemistry.nus.edu.sg/education/graduate/m-sc-programme-in-chemistry-for-energy-environment/

The MSc in Data Science and Machine Learning programme is offered jointly by the Department of Mathematics, the Department of Statistics and Applied Probability and the Department of Computer Science. This one-year programme will help to meet the growing demands for big-data professionals by transforming graduates with Bachelor degrees in quantitative science (e.g. mathematics, applied mathematics, statistics and physics) into practitioners.

The curriculum incorporates inter-disciplinary learning from computer science, mathematics and statistics. It also combines data analytics with machine learning. In addition to learning knowledge in data science, students will also have opportunities to explore the integration of machine learning and data analytics in sectors such as financial industry, healthcare and government.

Programme Structure

1. Students have to
   1. Read and pass five essential modules;
   2. Read and pass five elective modules from at least two Graduate Certificate (GC) tracks/clusters;

Module List

Five Essential Modules

• CS5224 Cloud Computing
• DSA4212 Optimisation for Large-Scale Data-Driven Inference
• DSA5101 Introduction to Big Data for Industry
• DSA5102X Foundations of Machine Learning
• DSA5201 DSML Industry Consulting and Applications Project

Five Elective Modules

Graduate Certificate in Deep Learning for Data Scientists

• DSA5202 Advanced Topics in Machine Learning
• DSA5204 Deep Learning and Applications (or CS5242 Neural Networks and Deep Learning)

Graduate Certificate in Data Mining for Industry

• CS5228 Knowledge Discovery and Data Mining
• ST5227 Applied Data Mining

Graduate Certificate in Big Data for Industry

• CS5344 Big-Data Analytics Technology
• ST5201 Statistical Foundations of Data Science

Graduate Certificate in Computer Vision

• CS4243 Computer Vision and Pattern Recognition
• CS5240 Theoretical Foundation of Multimedia
• DSA5203 Visual Data Processing and Interpretation

 Graduate Certificate in Data Science for Quantitative Finance

• QF5204 Numerical Methods in Quantitative Finance
• DSA5205 Data Science in Quantitative Finance
• ST5202 Applied Regression Analysis

 Graduate Certificate in Data Science for Internet of Things

• EE5022 Cyber Security for Internet of Things
• EE5024 IoT Sensor Networks
• EE5025 Intellectual Property: Innovations in IoT
• EE5027 Statistical Pattern Recognition
• ST5225 Statistical Analysis of Networks

 Graduate Certificate in Health Informatics

• SPH5414 Informatics for Health
• SPH5104 Healthcare Analytics
• SPH5411 Information Technology in Healthcare

 Cluster in Mathematics

• MA4230 Matrix Computation
• MA5232 Modeling and Simulations
• MA5266 Optimization

 Cluster in Statistics

• ST5207 Nonparametric Regression
• ST5210 Multivariate Data Analysis

 Cluster in Computing

• CS4248 Natural Language Processing
• CS5234 Algorithms at Scale
• CS5246 Text Mining
• CS5245 Big Data Systems for Data Science
• IS5152 Data Driven Decision Making

2. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

For admission and further details, please visit:

https://www.math.nus.edu.sg/graduates/m-sc-in-data-science-and-machine-learning/prospective-students/

The Master of Science in Financial Engineering (MFE) is a multi-disciplinary programme that combines finance, mathematics, and computing with a practical orientation to solve problems in finance. The MFE was launched in 1999 by the Centre for Financial Engineering at NUS, the predecessor to RMI. It aims to equip finance and banking industry professionals and fresh graduates with current knowledge and skills in financial innovations and technology. The domain knowledge includes financial product development, modelling of prices, hedging, investment technology, risk analyses and computational methods.

The degree is awarded by the National University of Singapore, administered through the Risk Management Institute (RMI) and comprises teaching staff from the Departments of Finance, Mathematics, Statistics and Applied Probability, Economics and practitioners from the finance industry. It is a multidisciplinary programme that draws from the established strengths of the various NUS Faculties.

 Programme Structure
To graduate from the programme, each candidate is required to complete 40 modular credits (MCs). Of these, there are five core (compulsory) modules and a compulsory financial engineering project equivalent to 4 MCs each. Candidates must also choose additional elective modules. There are also elective modules held overseas that are conducted at an intensive pace over one week.

Graduation Requirements

Students have to fulfill all the following conditions to graduate:

1. Read and pass the following six essential modules:
   • FE5101 Derivatives and Fixed Income
   • FE5107 Risk Analyses and Management
   • FE5110 Financial Engineering Project
   • FE5112 Stochastic Calculus and Quantitative Methods
   • FE5116 Programming and Advanced Numerical Methods
   • FE5209 Financial Econometrics
2. Read and pass four or more elective modules, totaling a minimum of 16 modular credits, from the following list:

• • FE5103 Equity Products and Exotics
  • FE5105 Corporate Financing and Risk
  • FE5211 Seminar in Financial Engineering
  • FE5216 Financial Technology Innovations Seminar
  • FE5219 Credit Analytics Practicum
  • FE5221 Trading Principles & Fundamentals
  • FE5222 Advanced Derivatives Pricing
  • FE5223 Introduction to Electronic Financial Market
  • FE5224 Current Topics in Applied Risk Management
  • FE5225 Machine Learning and FinTech
  • FE5226 C++ in Financial Engineering
  • FE5227 Commodities: Fundamentals and Modelling

For students admitted into the programme, a minimum Cumulative Average Point (CAP) of 3.00 is required for graduation.

Leave of Absence
A leave of absence may be granted to a candidate for up to one year only. A candidate who has to leave the programme for longer than that will need to withdraw from the programme. The leave of absence will be included in the maximum period of candidature.

Termination of Candidature
The candidature may be terminated if a candidate failed twice in the examination of a module, or failed in more than two modules throughout the course of study. No extension of the maximum period of candidature will be permitted. A candidate should also attain a minimum Cumulative Average Point (CAP) of 3.00 to remain in good standing.

For admission and further details, please visit: https://rmi.nus.edu.sg/masters-program/introduction.html

The MSc in Food Science and Human Nutrition  offers a comprehensive set of advanced topics including food bioscience (microbiology and safety, fermentation), modern food processing technology, evidence-based functional foods, modern analytical science and human nutrition. This programme is designed to provide professional continuing education training, which in turn better prepare the workforce amid the rapidly changing food landscape.

Programme Structure

A student must meet all the coursework and research project requirements and have earned 40 MCs with the following criteria:

• Achieve a minimum CAP of 3.0;
• Pass seven modules (minimum 5 FST-coded) from those listed in both module clusters of modules: 1) Food Science/Technology, 2) Nutrition
• For students admitted in AY2020/2021 Semester 2 (Jan 2021) and earlier: Successfully complete and attain a minimum of C+ grade for the module FST5199 MSc Research Project (12 MCs)
• For students admitted in AY2021/2022 Semester 1 (Aug 2021 onwards): FST5199 will not be offered. In the new syllabus, students need to pass FST5198 Advanced Food Science and Nutrition Seminar (4MC) AND obtain a minimum of C+ grade for one of the following:

• • FST5199A MSc Research Project (8MC) – to be completed over 1 or 2 semesters for full-time students

• • FST5199B Integrated Food Research Lab (8MC) – to be completed over 2 semesters

^From AY2021/2022 Semester 1 onwards, the modules with the suffix ‘A’ (i.e. FST5202A) will be offered in place of the corresponding modules without the suffix ‘A’ (i.e. FST5202).

*Subject to availability of quota and prerequisite requirements.

For admission and further details, please visit: https://www.fst.nus.edu.sg/education/postgraduate-programme/admission-information/msc-in-food-science-human-nutrition/

The MSc in Forensic Science aims to equip its participants with the key knowledge and capabilities to:

• Understand the fundamental concepts and principles behind the application of scientific techniques to forensic investigations and to the criminal justice system
• Explore the different basic and advanced techniques used in forensic investigation
• Enhance hands-on advanced problem solving skills by applying the knowledge gained to come up with innovative solutions to problems related to forensic science

Programme Structure

Students have to fulfil all the following conditions:

1. Read and pass the following two essential modules:
   1. FSC5199 Research Project in Forensic Science
   2. FSC5101 Survey of Forensic Science
2. Read and pass five* elective modules chosen from the following list:
   1. FSC5201 Advanced CSI Techniques
   2. FSC5202 Forensic Defense Science
   3. FSC5203 Digital Forensic Investigation
   4. FSC5204 Forensic Psychiatry and Psychology
   5. FSC5205 Forensic Science in Major Cases
   6. SP4261 Articulating Probability and Statistics in Court
   7. SP4262 Forensic Human Identification
   8. SP4263 Forensic Toxicology and Poison
   9. SP4264 Criminalistics: Evidence and Proof
   10. SP4265 Criminalistics: Forgery Expose with Forensic Science
   11. SP4266 Forensic Entomology
   12. FSC4206/LL4362V Advanced Criminal Litigation – Forensics on Trial
   13. IFS4102 Digital Forensics
3. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

*Please note that students can only read a maximum of 8 MCs of level 4000 electives.

For admission and further details, please visit: https://www.dbs.nus.edu.sg/education/master-of-science-in-forensic-science/

Master of Science in Mathematics by coursework is a postgraduate programme offered by the Department of Mathematics, which may be pursued full-time or part-time. This programme aims to provide advanced training in mathematics with an emphasis on coursework. It offers opportunities to those who have an Honours degree or a Bachelor’s degree in mathematics to build and enhance their professional skills and qualifications in advanced mathematics in general and/or in some specialised areas of applied mathematics.

Programme Structure

Students have to fulfil all the following conditions:

Track 1

1. EITHER
   1. Read and pass two MA modules at Level 4000 (or above) and eight MA modules at Level 5000 (or above);
      OR
   2. Read and pass two MA modules at Level 4000 (or above), six MA modules at Level 5000 (or above), and complete an individual project and written report (equivalent to 8 MC) over a maximum period of two semesters.
2. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

Track 2

1. EITHER
   1. Read and pass two MA modules at Level 3000 (or above), nine MA modules at  Level 4000 (or above) and nine MA modules at Level 5000 (or above);
      OR
   2. Read and pass two MA modules at Level 3000 (or above), nine MA modules at Level 4000 (or above), seven MA modules at Level 5000 (or above), and complete an individual project and written report (equivalent to 8 MC) over a maximum period of two semesters.
2. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

For admission and further details, please visit: https://www.math.nus.edu.sg/graduates/m-sc-in-mathematics-by-coursework/prospective-students/

NUS Department of Pharmacy has been running the Master of Science (Pharmaceutical Science and Technology) [MPST] programme since 2008. This part-time course-work based programme was initiated in response to directions from EDB to train science, pharmacy and engineering personnel to be proficient and knowledge-ready to meet the needs of the pharmaceutical / biopharmaceutical industry in Singapore. To make our students relevant in the future pharmaceutical / biopharmaceutical industry, we have adopted a broad-based approach in our curriculum, to encompass the various stages of pharmaceutical/biopharmaceutical development.

Programme Structure

Candidates admitted into the Master’s degree programme must read and pass a total of 10 modules (40 MC), comprising 5 core modules and 5 elective modules:

5 Core Modules, 4 MCs each:

• PR5198 Graduate Seminar Module in Pharmacy
• PR5211 Pharmaceutical Analysis IV
• PR5217 Formulation Science
• PR5218 Methodologies in Product Development (Capstone module)
• PR5304 Fundamental Topics in Pharmaceutical Science

5 Elective Modules, 4 MCs each; To be chosen from any of the following:

• PR5213 Pharmaceutical Process Validation
• PR5214 Advances in Tablet Technology
• PR5216 Advances in Drug Delivery
• PR5219 Product Development & Quality Management (new course title w.e.f. AY2020/2021, formerly known as “Product Quality Management”)
• PR5220 Bioprocess Technology
• PR5224 Pharmacoepidemiology
• PR5225 Preformulation Science
• PR5230 Pharmacoeconomics and Outcomes Research
• GMS5011 Fundamentals of Pharmaceutical Regulation (offered by Centre of Regulatory Excellence (CoRE), Duke-NUS Medical School)
• GMS5012 Chemistry, Manufacturing and Controls (offered by Centre of Regulatory Excellence (CoRE), Duke-NUS Medical School)

Graduation Requirements

To graduate with the degree in Master of Science (Pharmaceutical Science and Technology), candidates must have achieved a CAP of at least 3.00.

For admission and further details, please visit: https://pharmacy.nus.edu.sg/study/postgraduate-programmes/msc-pharmaceutical-science-technology-programme/

The Master of Science in Physics is a coursework programme initiated as a part-time programme in January 2000. It also can be enrolled on a full-time basis now.

Programme Structure

A candidate in the MSc Programme in Physics by coursework must complete the following in order to be awarded the MSc degree:

Track 1 : 40 modular-credit programme (for applicants who have an Honours degree or equivalent qualifications)

EITHER

1. Read and pass five PC level 5000 modules (excluding PC5198) amounting to 20 MCs and at least 8 MCs must be from the following list of modules. Subject to approval, students are allowed to choose not more than 12 MCs from level 5000 modules offered by other Departments.
   • PC5201 Advanced Quantum Mechanics
   • PC5202 Advanced Statistical Mechanics
   • PC5203 Advanced Solid State Physics
   • PC5210 Advanced Dynamics
   • PC5214 Principles of Experimental Physics
2. Read and pass two PC level 4000 modules amounting to 8 MCs
3. Complete a research project PC5288 equivalent to 12 MCs
4. Obtain a minimum Cumulative Average Point (CAP) of 3.00

OR

1. Read and pass eight PC level 5000 modules (excluding PC5198) amounting to 32 MCs and at least 8 MCs must be from the following list of modules. Subject to approval, students are allowed to choose not more than 12 MCs from level 5000 modules offered by other Departments.
   • PC5201 Advanced Quantum Mechanics
   • PC5202 Advanced Statistical Mechanics
   • PC5203 Advanced Solid State Physics
   • PC5210 Advanced Dynamics
   • PC5214 Principles of Experimental Physics
2. Read and pass two PC level 4000 modules amounting to 8 MCs
3. Obtain a minimum Cumulative Average Point (CAP) of 3.00

Track 2: 80 modular-credit programme (for applicants who have a Bachelor’s pass degree or completed a three-year study in physics)

EITHER

1. Read and pass five PC level 5000 modules (excluding PC5198) amounting to 20 MCs and at least 8 MCs must be from the following list of modules. Subject to approval, students are allowed to choose not more than 12 MCs from level 5000 modules offered by other Departments.
   • PC5201 Advanced Quantum Mechanics
   • PC5202 Advanced Statistical Mechanics
   • PC5203 Advanced Solid State Physics
   • PC5210 Advanced Dynamics
   • PC5214 Principles of Experimental Physics
2. Read and pass eight PC level 4000 modules amounting to 32 MCs
3. Read and pass one PC level 4000 module or PC level 5000 module amounting to 4 MCs
4. Read and pass three PC level 3000 modules amounting to 12 MCs
5. Complete a research project PC5288 equivalent to 12 MCs
6. Obtain a minimum Cumulative Average Point (CAP) of 3.00

OR

1. Read and pass eight PC level 5000 modules (excluding PC5198) amounting to 32 MCs and at least 8 MCs must be from the following list of modules. Subject to approval, students are allowed to choose not more than 12 MCs from level 5000 modules offered by other Departments.
   • PC5201 Advanced Quantum Mechanics
   • PC5202 Advanced Statistical Mechanics
   • PC5203 Advanced Solid State Physics
   • PC5210 Advanced Dynamics
   • PC5214 Principles of Experimental Physics

1. Read and pass eight PC level 4000 modules amounting to 32 MCs
2. Read and pass one PC level 4000 module or PC level 5000 module amounting to 4 MCs
3. Read and pass three PC level 3000 modules amounting to 12 MCs
4. Obtain a minimum Cumulative Average Point (CAP) of 3.00

For admission and further details, please visit:

https://www.science.nus.edu.sg/admissions/graduates/coursework-programmes/application-information/

The Master of Science in Quantitative Finance by coursework is a postgraduate programme offered by the Department of Mathematics with the cooperation of the Department of Economics and the Department of Statistics and Applied Probability. The objective of the programme is to provide advanced training in quantitative finance with an emphasis on coursework. Students in the programme are expected to acquire advanced knowledge in quantitative finance as well as a deep understanding of the background and implications of the use of quantitative methods in the financial industry. The programme offers opportunities to those who have an Honours degree in quantitative finance or mathematics to build and enhance their professional skills and qualifications in quantitative finance at masters level.

Programme Structure

Students have to fulfil all the following conditions:

1. Read and pass the following five essential modules:
   1. MA4269    Mathematical Finance II
   2. QF4102    Financial Modelling
   3. QF5202  Structured Products
   4. QF5203  Risk Management
   5. QF5210    Financial Time Series: Theory and Computation
2. Read and pass five elective modules chosen from the following list:
   1. DSA5205 Data Science in Quantitative Finance
   2. MA5233  Computational Mathematics
   3. MA5248  Stochastic Analysis in Mathematical Finance
   4. QF5201  Interest Rate Theory and Credit Risk
   5. QF5204 Numerical Methods in Quantitative Finance
   6. QF5205 Topics in Quantitative Finance I
   7. QF5206 Topics in Quantitative Finance II
   8. QF5207 Investment and Portfolio Selection
   9. QF5208 AI & FinTech
   10. QF5401 Graduate Internship in Quantitative Finance I
   11. QF5402 Graduate Internship in Quantitative Finance II
   12. EC5102 Macroeconomic Theory
   13. EC5103 Econometric Modelling & Applications I
   14. EC5332R Money and Banking
   15. ECA5334 Corporate Finance
   16. ST5207 Non-parametric regression
   17. ST5210 Multivariate Data Analysis
   18. ST5218 Advanced Statistical Methods in Finance
3. Obtain a minimum Cumulative Average Point (CAP) of 3.00 00 or an average grade of at least  B-.

Modules coded MAxxxx or QFxxxx are offered by the Department of Mathematics. Modules with codes QF5xxx and DSA5205 are offered exclusively to students in the Master of Science in Quantitative Finance programme.

Modules coded ECxxxx or ECAxxxx are offered by the Department of Economics.

Modules coded STxxxx are offered by the Department of Statistics and Applied Probability.

For admission and further details, please visit: https://www.math.nus.edu.sg/graduates/m-sc-in-quantitative-finance-by-coursework/prospective-students/

The program is offered by the Department of Mathematics, National University of Singapore (NUS), in collaboration with the School of Mathematical Sciences at the Shanghai Jiao Tong University (SJTU). Teaching will be conducted primarily in the campus of SJTU.

The programme aims at developing talented graduates with international outlook and high foreign language proficiency levels, who have in-depth knowledge in quantitative finance and are also capable of tackling practical issues of the financial industry in China. This programme is a 40-modular credit (MC) programme consisting of five essential modules and five elective modules. Each module carries 4 MC, and comprises 12 sessions of 3-hour lecture, plus midterm and final exams, and continuous assessment(s). The five essential modules are all offered by NUS. Students may choose any five modules from the list of elective modules offered by NUS and SJTU.

Programme Structure

Students have to fulfil all the following conditions:

1. Read and pass the following five essential modules:
   1. MA4269A    Mathematical Finance II
   2. QF4102A     Financial Modelling
   3. QF5202A     Structured Products
   4. QF5203A     Risk Management
   5. QF5210A     Financial Time Series: Theory and Computation
2. Read and pass five elective modules chosen from the following list:
   1. QF5201A   Interest Rate Theory and Credit Risk
   2. QF5205A  Topics in Quantitative Finance I
   3. QF5206A  Topics in Quantitative Finance II
   4. QF5207A  Investment and Portfolio Selection
   5. QF5310    Data Analysis and Machine Learning in Finance
   6. QF5311    Advanced Methods in Risk Management
   7. QF5312  Statistical Models and Methods in Finance
   8. QF5313  Advanced Computational and Programming Methods in Finance
   9. QF5314  Basic Mathematics in Quantitative Finance
   10. QF5315  Selected topics in Fintech
   11. QF5401 Graduate Internship in Quantitative Finance I
   12. QF5402 Graduate Internship in Quantitative Finance II
3. Obtain a minimum Cumulative Average Point (CAP) of 3.00 or an average grade of at least B-.

Modules with codes beginning with MA or QF are offered by the Department ofMathematics, National University of Singapore. Modules with codes QF5xxxx areoffered exclusively to students in the Master of Science in Quantitative Financeprogramme.

Modules with codes beginning with QF53xx are offered by the School of Mathematical Sciences, Shanghai Jiao Tong University.

For admission and further details, please visit: https://www.math.nus.edu.sg/graduates/m-sc-in-quantitative-finance-nus-sjtu-mqf/prospective-students/

For students admitted in AY2020 and before

The objective of the programme is to provide a sound knowledge of the statistical principles and methods required by practising statisticians.

Programme Structure

Track 1
Students have to fulfil the following conditions:

• Read and pass the following two essential modules amounting to 8 MCs:
  • ST5201 Basic Statistical Theory
  • ST5202 Applied Regression Analysis
• Read and pass eight ST level 5000 modules or higher amounting to 32 MCs
• Obtain a minimum Cumulative Average Point (CAP) of 3.00

A candidate who has an Honours degree in Statistics or Mathematics might be exempted from reading one or more compulsory modules upon the approval of the Head of Department of Statistics and Applied Probability, but an exempted module must be replaced by an elective module.

Track 2
Only the full-time programme will be offered for this track.

Students have to fulfil the following conditions:

• Read and pass six ST level 4000 modules amounting to 24 MCs. Subject to department approval, not more than two modules can be taken from other departments.
• Read and pass ten ST level 5000 modules amounting to 40 MCs
• Complete a project ST5199 amounting to 16 MCs
• Obtain a minimum Cumulative Average Point (CAP) of 3.00

For students admitted in AY2021 and after

To graduate from the Programme, each candidate is required to read and pass five core modules, and five elective modules.

A minimum Cumulative Average Point (CAP) of 3.00 is required for graduation.

For admission and further details of the latest intake, please visit: https://www.stat.nus.edu.sg/prospective-students/graduate-programme/m-sc-by-coursework-programme/

This programme is available in full-time and part-time mode. The primary objective of the NUS Doctor of Pharmacy (PharmD) programme is to train pharmacy practitioners to possess leadership qualities, advanced expertise and clinical experience that enable them to be at the forefront of the Pharmacy profession and health care in a variety of settings – institutional, community practice, government, academia, industry, translational research and drug development. The curriculum emphasizes a patient-centred course of study and involves a structure that will enable the students to develop into reflective practitioners with skills and attitudes to evaluate critically and modify practices in a timely and effective manner.

Programme Structure

1. Length of Study

Full-Time Programme may be completed over 2 academic years. The didactic component may be completed during the first 10-months followed by the clerkship rotations over the following 40-50 weeks.

Part-Time Programme may be completed over 3-6 academic years. The didactic component may be completed over a period of 2-3 academic years.

2. Curriculum

The didactic component of the programme consists of 16 modules, comprising 10 essential Level 5000 modules and 5 elective Level 5000 modules as described below. Students must read the 10 essential Level 5000 modules and choose upto 3 elective Level 5000 modules

Didactic Coursework

Essential Modules (38 MC)

• PR5135 Foundations in Advanced Pharmacy Practice (4 MC)
  • Statistics, research methodology, clinical research, drug information, literature evaluation, quality improvement, drug use evaluation
• PR5134 Advanced Skills in Pharmacy Practice (4 MC)
  • History taking, clinical documentations, communication skills, basic physical assessment skills, simulation-based training
• PR5136 Pharm.D. Seminar & Teaching (4 MC)
  • Presentation skills, peer evaluation, teaching of undergraduate students
• PR5113 Clinical Pharmacokinetics and Therapeutic Drug Monitoring (4 MC)
  • Basic pharmacokinetics, pharmacokinetics and dynamics in renal impairment, hepatic impairment, logy, vancomycin, aminoglycosides, antiepileptics, immunosuppressants, antifungals
• PR5130 Advanced Pharmacotherapy I (2 MC)
  • Infectious diseases, hepatology
• PR5131 Advanced Pharmacotherapy II (2 MC)
  • Acute cardio, stroke, fluid and electrolytes
• PR5132 Advanced Pharmacotherapy III (2 MC)
  • Oncology & supportive care
• PR5133 Advanced Pharmacotherapy in Special Populations (2 MC)
  • Pediatrics, women’s health
• PR5137 Advanced Pharmacotherapy in Geriatrics (2 MC)
• PR5239 Clinical Pharmacy Research Project (12 MC)
  • Study design, IRB application, data collection and analysis, research report, presentations.

Elective Modules (6 MC) – undertake 2 to 3 elective modules to make up 6 MC

• PR5230A Pharmacoecomomics (2 MC)
• PR5230B Outcomes Research (2 MC)
• PR5237 Management of Older Patients (2 MC)
• PR5131A Advanced Pharmacotherapy IIA (2 MC)
  • Emergency medicine and critical care
• PR5132A Advanced Pharmacotherapy IIIA (2 MC)
  • Haematology and immunology

Clerkships

All PharmD candidates must complete 40 weeks of clerkship consisting eight 5-week attachments at various practice settings. The clerkship component of the programme aims to provide hands-on application of the knowledge gained in the didactic modules, and to develop the clinical skills necessary to provide advanced pharmaceutical care.

• Compulsory clerkships (20 MC) (5 weeks each, total of 20 weeks)
  This will consist of clerkships in the following areas:
  • PR5150  Ambulatory Care (5 MC)
  • PR5151  Adult Acute Care Medicine (5 MC)
  • PR5152  Adult General Medicine (5 MC)
  • PR5154  Drug Information (5 MC)
• Elective clerkships (20 MC) (5 weeks each, total of 20 weeks)
  This will consist of four 5-week attachments to allow students to gain exposure to a broad range of pharmacy practice settings, as well as to allow them to pursue areas of personal interest.  Options for elective clerkships will depend on available resources and clerkship sites.
  • PR5250  Elective Clerkship I (5 MC)
  • PR5251  Elective Clerkship II (5 MC)
  • PR5252  Elective Clerkship III (5 MC)
  • PR5253 Elective Clerkship IV (5 MC)

Graduation Requirements

Candidates will need to complete 44 MC worth of modules plus clerkships (40 MC) as indicated in the curriculum. To graduate with the PharmD degree, the candidate must have achieved an average CAP of at least 3.5 for all essential and elective modules, in addition to passes for all eight clinical clerkships.

For admission and further details, please visit: https://pharmacy.nus.edu.sg/study/postgraduate-programmes/doctor-of-pharmacy-pharm-d/