Master Programme in Applied Computational Science, Environmental Science

Utbildningsfakta

Kod: NATBE

<p>Does the opportunity to immerse yourself in environmental science and advanced computations appeal to you? This Master’s programme gives you knowledge in how to use numerical simulations and machine learning to make forecasts and analyses, or to replace experiments. You can learn how to generate and store large amounts of data and use data science to search for patterns, connections, and trends in issues related to the environment.</p><p>Advanced computations are increasingly important in research and business. On this Master’s programme you will learn how to study complex processes within the natural sciences, and how computational science can contribute to knowledge evolution in society. Some examples of angles to focus on could be environmental and climate change, climate adaptation, biodiversity and ecosystem services, environmental protection or chemical risks. In addition to theory for computational science, there will be an emphasis on obtaining knowledge about the practical tools that are used by professionals in the field, including training your skills in programming.</p> <p>The programme will prepare you for a professional career in academia as well as in business and industry. The Master’s programme gives you specialised knowledge in the field of computational science, while also being interdisciplinary in character. You will take courses alongside students from other specialisations, and there will be a chance to conduct joint projects and degree projects. You will take advanced courses in environmental science in order to build on your subject knowledge from your Bachelor’s degree.</p> <p>You will get general knowledge and skills of importance for computationally intensive professions, such as problem formulation, information searching, data processing, scientific writing, and presentation techniques. The programme has strong ties with research. You will be taught by internationally well-recognised researchers, and you will be in contact with several research groups. The programme is taught in English.</p> <p><strong>Programme structure</strong><br /> In your first year, you study one semester of introductory courses in mathematics, statistics and programming which will give you knowledge to conduct projects in computational science. You then go on to specialise in applied computational science and environmental science with courses that build on your Bachelor’s degree.</p> <p>During the second year, you focus on courses in modelling in computational science and reproducible data analysis and statistical learning. Elective courses include ecosystem modelling, Bayesian methods or introduction to artificial neural networks and deep learning. The last semester is reserved for the Master’s thesis.</p> <p><strong>Career opportunities</strong><br /> Graduates of the programme can embark on several different career paths. The Master’s programme gives you a solid foundation for third-cycle education in the natural sciences, or a career within industry or business. You can thus also choose a career path outside academia and then find attractive jobs in areas where there is a need to solve natural science problems with the help of statistics, data processing or simulations, in industry or in public administration and other organisations.</p><p>https://www.maths.lu.se/english/education/masters-programme-in-applied-computational-science/</p>

Behörighet

Specialisation Environmental Science Bachelor´s degree of at least 180 credits, including 90 credits in science of which 15 credits should be in mathematics and 30 credits should be in environmental science. Proficiency in English equivalent to English 6/B from Swedish upper-secondary school. Other information Some of the optional courses within the program may have higher requirements in mathematics or in other natural science subjects.

Utbildningstillfällen

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• Master Programme in Applied Computational Science, Environmental Science

  Lund University

  Startdatum: 31 augusti 2026

  Slutdatum: 4 juni 2028

  Studietakt: 100 %