MSci mathematics & computer science

5 Years On Campus Bachelors Program

University of Lincoln

Program Overview

The MSci Mathematics & Computer Science is a four-year integrated master’s degree that combines advanced mathematics with high-level computing and programming skills. It’s ideal for students who want to tackle complex quantitative problems, develop sophisticated computational solutions, and prepare for research, technology, data science, or finance-focused careers.

Curriculum Structure

Years 1‑2

The first two years provide a strong foundation in mathematics and computer science. Mathematics modules include Calculus, Linear Algebra, Probability and Statistics, and Introduction to University Mathematics. Computing modules cover Programming Fundamentals, Computer Systems, Algorithms, and Problem-Solving Techniques. Students develop analytical reasoning and core programming skills to support higher-level study.

Year 3

The third year introduces advanced mathematical and computational topics. Mathematics modules may include Complex Analysis, Differential Equations, Numerical Methods, and Stochastic Processes. Computer science modules cover Data Structures and Algorithms, Object-Oriented Programming, Machine Learning, and Software Engineering. Students also engage in projects that integrate both mathematics and computing skills.

Year 4 (Master’s Year / Honours Level)

The final year focuses on high-level topics and independent research. Mathematics modules include Topology, Partial Differential Equations, Mathematical Modelling, and Advanced Stochastic Processes. Computer science modules may include Advanced Machine Learning, Artificial Intelligence, and Computational Modelling. Students complete a substantial Research Project, demonstrating mastery of mathematical theory, computational methods, and applied problem-solving.

Focus Areas

Advanced mathematics, pure and applied mathematics, probability and statistics, calculus, differential equations, numerical methods, programming, algorithms, software engineering, machine learning, computational modelling, research-based problem solving.

Learning Outcomes

Graduates develop advanced analytical, computational, and problem-solving skills, capable of designing and implementing solutions to complex quantitative problems. They are prepared for roles in software development, data science, analytics, finance, research, and engineering, or for postgraduate study in mathematics, computer science, or related disciplines.

Professional Alignment (Accreditation)

While not tied to a specific professional accreditation, this degree equips students with skills highly valued in research, technology, data analytics, finance, and quantitative careers. Graduates are also well-prepared for postgraduate study or professional qualification pathways in mathematics and computing.

Reputation (Employability & Outcomes)

The MSci Mathematics & Computer Science degree is recognized for producing graduates with both deep mathematical knowledge and advanced computational skills. Alumni often pursue careers in technology, data science, finance, research, and analytics, benefiting from the rigorous curriculum and integrated project experience.

Experiential Learning (Research, Projects, Internships etc.)

The MSci Mathematics & Computer Science programme at Lincoln is an advanced, integrated master’s-level course that builds on the BSc foundation, combining rigorous mathematics with in-depth computer science and computational skills. Over four years, you study pure and applied mathematics, software development, algorithm design, data analysis, and computational modelling. The degree emphasizes hands-on learning, giving you real-world technical experience, research-oriented projects, and the skills to tackle complex problems across mathematics and computing domains.

You graduate as a highly versatile professional, capable of bridging analytical mathematics and software/computational solutions — ready for research, industry, or postgraduate study.

Transition to bullet points: Here’s a breakdown of the practical, hands-on, and research-oriented experiences embedded in the programme:

Experiential Learning Highlights

Comprehensive mathematics and computing foundation: Early years cover algebra, calculus, linear algebra, probability, statistics, differential equations, numerical methods, and introductory programming.
Advanced mathematics modules: Later years include applied mathematics, mathematical modelling, and numerical analysis, allowing students to develop specialised analytical skills.
Advanced computer science and programming: You gain in-depth knowledge in algorithms, software engineering, database systems, programming languages, and computational problem-solving.
Individual research/project module: In the final year, students undertake a substantial independent project that integrates mathematics and computer science — for example, software development, data modelling, simulations, or applied mathematical research.
Group projects and collaborative learning: Throughout the degree, students complete team-based coding and mathematical modelling assignments, enhancing collaboration, communication, and problem-solving skills.
Computational and digital tools: Students use industry-standard software, programming platforms, and simulation tools to solve mathematical and computational problems.
Small-group tutorials and workshops: Weekly tutorials and problem-solving sessions support understanding of advanced concepts, coding techniques, and mathematical reasoning.
Optional placement opportunities: Students can choose to take a placement year in industry or research, applying mathematics and computational skills in real-world environments.
Research-informed teaching: Modules are shaped by staff research, ensuring learning reflects current developments in mathematics, computational mathematics, and computer science.
Transferable skills development: You gain strong analytical reasoning, coding, modelling, project management, communication, and critical thinking skills applicable in technology, finance, research, and analytical careers.
Interdisciplinary integration: The programme emphasizes connections between mathematics and computing, preparing students for roles that require both analytical and computational expertise.

Progression & Future Opportunities

Graduates of the MSci Mathematics & Computer Science programme gain an advanced integrated education in mathematics and computing, including in-depth study of algorithms, data structures, programming, and mathematical modelling. The MSci is designed for students aiming for research, technical leadership, or highly specialised roles in industry, giving them a competitive edge in technology, data science, finance, and analytics sectors.

Typical career roles include:

Software Developer / Lead Programmer
Data Scientist / Senior Data Analyst
Quantitative Analyst / Computational Finance Specialist
Research Analyst / Scientific Computation Specialist

University support for employability:

Careers & Employability Services: personalised guidance, CV building, interview coaching, and employer networking.
Peer-support workshops and clubs: strengthen problem-solving, programming, teamwork, and computational skills.
Industry-linked projects and competitions: hands-on experience working on practical problems to showcase skills to employers.
Global opportunities: optional study abroad, internships, or collaborative international projects to enhance professional exposure.

Employment statistics & salary outcomes:

MSci graduates are highly employable, with a majority securing professional roles or further study within 15 months of graduation.
Typical starting salaries range from £30,000–£35,000, reflecting the advanced skills and research experience gained.
Graduates enter roles in software development, AI, data analytics, financial modelling, IT consulting, and research sectors.

Industry relevance & long-term value:

Advanced study in both mathematics and computer science provides versatility for careers in high-tech, finance, AI, data science, and research-intensive industries.
The programme’s focus on applied projects and research strengthens problem-solving and independent analytical skills, highly valued by employers.
Graduates acquire skills that remain relevant in evolving sectors, including algorithm design, computational modelling, and data analysis.

Graduation outcomes:
Graduates leave with comprehensive knowledge of mathematics, computer science, programming, and computational problem-solving, ready for technical, analytical, or research-oriented careers, or further academic study at the postgraduate level.

Further Academic Progression:

After completing this programme, students can pursue:

PhD or research degrees in Computational Mathematics, Data Science, Artificial Intelligence, Machine Learning, or Applied Mathematics.
Specialised Master’s programmes in Computer Science, Data Science, Quantitative Finance, or AI.
Direct entry into senior roles in technology, analytics, finance, research, or software development, leveraging both advanced theoretical and applied skills.