BSc (hons) mathematics & computer science

The BSc Mathematics & Computer Science programme at Lincoln combines rigorous mathematical theory with practical computing skills. You gain strong foundations in pure and applied mathematics while developing coding, algorithmic, and computational thinking expertise. The degree emphasizes hands-on learning through programming labs, computational modelling, group projects, and an individual research or software development project in the final year.

This dual-focus prepares you for careers that require both quantitative and technical expertise, including data analytics, software development, financial modelling, research, and engineering applications. You graduate not only as a mathematician but also as a capable computer scientist with strong problem-solving and computational skills.

Transition to bullet points: Here’s a clear breakdown of the practical, hands-on, and technology-focused experiences integrated into the programme:

Experiential Learning Highlights

• Mathematics foundation: Core modules include algebra, calculus, linear algebra, probability, statistics, differential equations, and numerical methods, building analytical and problem-solving skills.

• Programming and computational skills: Students learn programming languages, software development, algorithm design, and computational mathematics through hands-on coding labs and projects.

• Applied computational mathematics: Practical modules involve modelling, simulations, and numerical methods using computing tools to solve real-world mathematical problems.

• Group projects and collaborative learning: Students work on team-based coding, mathematical modelling, or software development assignments, developing teamwork and communication skills.

• Individual research or development project: In the final year, students complete an independent project that may involve software development, computational modelling, or applied mathematics research, giving experience in project planning, coding, and reporting results.

• Small-group tutorials and problem-solving sessions: Weekly tutorials and workshops reinforce mathematical concepts, computational techniques, and programming skills.

• Optional placement opportunities: Students may choose to take a placement year in industry or research, applying mathematics and computer science skills in professional or research environments.

• Transferable skills: The degree develops critical thinking, analytical reasoning, coding, modelling, problem formulation, and project management skills highly valued in technology, finance, and research sectors.

• Modern digital learning environment: Access to computing labs, software tools, online coding platforms, and simulation environments supports independent and guided learning.

• Interdisciplinary approach: By integrating mathematics and computer science, the programme encourages students to connect abstract mathematical theory with computational problem-solving, preparing for technical and analytical careers.

Graduates of Mathematics & Computer Science develop strong mathematical reasoning alongside programming, algorithms, and computational problem-solving skills. This combination prepares students for careers in technology, data analytics, software development, finance, and research, providing highly adaptable skills for a range of industries.

Typical career roles include:

• Software Developer / Programmer

• Data Scientist / Data Analyst

• Quantitative Analyst / Financial Modeller

• Research Analyst / Computational Scientist

University support for employability:

• Careers & Employability Services: personalised guidance, CV preparation, interview coaching, and employer networking opportunities.

• Peer-support workshops and clubs: focus on problem-solving, programming, teamwork, and computational skills.

• Industry-linked projects and competitions: practical opportunities to showcase skills to employers and gain hands-on experience.

• Study abroad and internships: optional global mobility programmes and internships to gain international exposure and professional experience.

Employment statistics & salary outcomes:

• Around 80% of graduates secure professional employment or further study within 15 months of graduation.

• Typical starting salaries range from £28,000–£32,000, with strong growth potential in technology or finance sectors.

• Graduates work in software development, data science, analytics, finance, IT consulting, and research roles.

Industry relevance & long-term value:

• The combination of mathematics and computer science provides a versatile skill set applicable to finance, technology, AI, data analytics, and research.

• Applied learning and practical experience prepare graduates for professional challenges and emerging industries.

• Computational, analytical, and problem-solving skills remain highly relevant across evolving sectors.

Graduation outcomes:
Graduates leave with a strong foundation in mathematics, programming, algorithms, and data analysis, ready for technical, analytical, or research-oriented careers in multiple sectors globally.

Further Academic Progression:

After completing this programme, students can pursue:

• Master’s degrees in Computer Science, Data Science, Applied Mathematics, Artificial Intelligence, or Quantitative Finance.

• Research degrees (MSc/PhD) in computational mathematics, machine learning, data analytics, or related STEM fields.

• Direct entry into professional careers in software development, IT, data analytics, finance, or research, leveraging strong programming and analytical expertise.