Introduction
Develop scientific literacy and data-driven skillsets to become an expert in analysing, modelling, and interpreting planetary and space-related data. Learn to explore planetary systems and extract insights from complex datasets in a rapidly evolving scientific landscape.
The MSc combines advanced data analytics with planetary and space sciences. You will gain a strong foundation in planetary science, remote sensing imagery, big data analysis, machine learning, and computational modelling, working with real-world planetary and Earth observation datasets.
Designed to meet the growing demand for data-literate planetary scientists and scientifically literate data professionals, you will learn how to explore planetary systems and extract insights from complex data in a rapidly evolving scientific landscape.
You’ll study alongside graduates from a wide range of disciplines, including Earth science, computing, mathematics, physics, and engineering, and be well prepared for doctoral study or data-driven careers in space agencies, research institutions, environmental organisations, and tech companies.
Available Programmes of Study
- MSc
-
Planetary and Data Sciences
- Qualification
- MSc
- Duration
- 12 months
- Learning Mode
- On Campus Learning
- Study Mode
- Full Time
- Start Month
- September
- Location
- Aberdeen
- Qualification
- MSc
- Duration
- 12 months
- Learning Mode
- On Campus Learning
- Study Mode
- Full Time
- Start Month
- January
- Location
- Aberdeen
Programme Fees
Please refer to our Tuition Fees page for fee information for this programme, or contact us via the Enquire Now form.
Semester 1
Semester 1: Compulsory Courses
- Getting Started at the University of Aberdeen (PD5506)
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This course, which is prescribed for all taught postgraduate students, is studied entirely online, takes approximately 2-3 hours to complete and can be taken in one sitting, or spread across the first 4 weeks of term.
Topics include University orientation overview, equality & diversity, MySkills, health, safety and cyber security, and academic integrity.
Successful completion of this course will be recorded on your Transcript as ‘Achieved’.
- Introduction to Programming (PX5507)
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15 Credit Points
This course teaches programming in high level languages and in particular the Wolfram Language (Mathematica). It will introduce all areas of this powerful language, including symbolic and numerical calculations and simulations, links to other high level languages such as R and Python, links to database languages mySQL and Mongo.
We will show how Wolfram Language allows computation to be applied to many areas of data analysis, and modelling. This allows us to gain deep insight into systems.
- Statistics and Time Series Analysis (PX5710)
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15 Credit Points
This is an introductory course in statistics and statistical methods for data analysis.
We will introduce descriptive statistics, ANOVA, GLMs, correlations, spectra, wavelets, etc.
This will allow us to perform typical analysis that underlie most modern data science questions.
- Space Weather and Radiation for Planetary Exploration (GL5562)
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15 Credit Points
Space weather describes the varying conditions in the space environment between the sun and Earth. Phenomena associated with space weather have the potential to impact systems and technologies in orbit and on Earth. For example, solar energetic particles can penetrate satellite electronics and cause electrical failure. These energetic particles also block radio communications at high latitudes during solar radiation storms. Each phenomenon of space weather impacts a different technology.
In this course, we will review Space Weather on Earth, and we will use the lessons learned to understand the impact of the space environment on planetary exploration.
- Astrobiology, Biogeochemistry and Geobiology for Explorers (GL5563)
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15 Credit Points
This course will explore the origins and likely extent of life on Earth and in the Solar System. We will begin by discussing the elements and building blocks of life and processes that can make precursors of life (e.g. amino acids). We will then discuss how microbial life may be fossilised and how to identify ancient and extra-terrestrial signs of life. We will make use of our excellent analytical facilities to show how biotic signals can be distinguished from abiotic effects, including exploring organic carbon biomarkers, and using examples of fossilisation of microorganisms by siliceous and carbonate minerals from lakes, streams, hot-springs and oceans. From there, we will be able to explore potentially habitable environments of our Solar System, and learn about current and future astrobiological exploration missions (Martian rovers and orbiters, asteroid, comets, sample return, ocean worlds…)
Semester 2
Planetary and Data Science Project (60 credit points)
Semester 3
Semester 3: Compulsory Courses
- Comparative Planetology and the Atmosphere of Earth (GL5062)
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15 Credit Points
In this course, we will cover how studies of the other planets of the solar system have helped us understand Earth's atmosphere. We will review the fundamental physical and chemical processes in planetary atmospheres, and we will provide an up-to-date overview of modelling, observation methods and missions to study planetary atmospheres.
- Advanced Statistics and Special Applications (PX5020)
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15 Credit Points
The goal of this course is to teach you advanced concepts and techniques in statistics, focusing on applying them to real data.
Semester 3: Optional Courses
One from: PX5019 Data Visualisation and PX5023 Image Analysis
Plus one from: GL5063 Basics of Remote Sensing and Geospatial Analysis and GL5064 Spectroscopy, Radiative Transfer and Retrieval
- Data Visualisation (PX5019)
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15 Credit Points
Visualising the outcome of a data analysis is critical to communicate the results. In this course we will study standard and cutting edge visualisation techniques to make sense of data, and present it in a compelling, narrative-focused story.
Presenting and visualising data and reporting on the result of an analysis are a crucial skill when making sense of data.
- Image Analysis (PX5023)
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15 Credit Points
Nowadays a large volume of data is stored in form of images. This course introduces the tools needed to analyse images and extract information from them, including aspects of image enhancement, filtering, segmentation, morphological analysis and image classification based on convolutional neural networks.
- Basics of Remote Sensing and Geospatial Analysis (GL5063)
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15 Credit Points
This course will provide an overview of planetary remote sensing principles and methods. The students will be trained on performing geospatial integration and analysis of different spatial datasets. This course introduces the students to the theoretical problems and practice of data capture, handling and methods of analysis of spatial data.
- Spectroscopy, Radiative Transfer and Retrieval (GL5064)
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15 Credit Points
Spectroscopy, radiative transfer and retrieval methods are rapidly growing fields with extreme importance in atmospheric and planetary science. They are fundamental to study weather, climate, air quality on Earth, the evolution of greenhouse gases and biogeochemical cycles on Earth. They provide information about the physics and evolution of the atmospheres of the solar system planets and exoplanets at a larger scale. This course will provide the fundamental knowledge to a depth that will leave a student with the background to perform quantitative research on atmospheres. It spans across principles through applications, with sufficient background for students without prior experience in spectroscopy or radiative transfer.
We will endeavour to make all course options available. However, these may be subject to change - see our Student Terms and Conditions page. In exceptional circumstances there may be additional fees associated with specialist courses, for example field trips.
Fee Information
Scholarships
All eligible self-funded international Postgraduate Masters students will receive an £8,000 scholarship. Learn more about this Aberdeen Global Scholarship here.
To see our full range of scholarships, visit our Funding Database.
How You'll Study
Learning Methods
- E-learning
- Group Projects
- Individual Projects
- Lab Work
- Lectures
- Research
- Tutorials
- Workshops
Assessment Methods
You will be assessed through a mix of methods. These may include online quizzes and multiple-choice tests, written assignments, technical reports and data analysis exercises.
You can also expect presentations and oral assessments, group-based activities, and project work.
Why Study Planetary and Data Sciences?
- Develop in-demand technical skills in remote sensing, satellite and planetary mission data analysis, machine learning, big data analytics, and computational modelling.
- Learn from the combined strengths of the University of Aberdeen’s established MSc Data Science and MSc Planetary Science programmes, taught jointly by experts from the School of Natural and Computing Sciences and the Department of Geosciences.
- Train as a genuinely interdisciplinary scientist, working across geosciences, computing, physics, mathematics, chemistry and biology, and learning to translate between domain science and data-driven approaches.
- Prepare for careers in space agencies, research institutes, satellite and Earth observation companies, environmental data services, climate modelling centres, and tech and analytics sectors.
- Build a strong foundation for doctoral research in planetary science, astroinformatics, geospatial data science, or AI for science.
Interested in this programme?
Entry Requirements
Qualifications
The information below is provided as a guide only and does not guarantee entry to the University of Aberdeen.
2:2 (lower second class) Honours degree or equivalent in any subject will be considered.
Please enter your country or territory to view relevant entry requirements.
English Language Requirements
To study for a Postgraduate Taught degree at the University of Aberdeen it is essential that you can speak, understand, read, and write English fluently. The minimum requirements for this degree are as follows:
IELTS Academic:
OVERALL - 6.5 with: Listening - 5.5; Reading - 5.5; Speaking - 5.5; Writing - 6.0
TOEFL iBT:
OVERALL - 90 with: Listening - 17; Reading - 18; Speaking - 20; Writing - 21
PTE Academic:
OVERALL - 62 with: Listening - 59; Reading - 59; Speaking - 59; Writing - 59
Cambridge English B2 First, C1 Advanced, C2 Proficiency:
OVERALL - 176 with: Listening - 162; Reading - 162; Speaking - 162; Writing - 169
Read more about specific English Language requirements here.
Document Requirements
You will be required to supply the following documentation with your application as proof you meet the entry requirements of this degree programme. If you have not yet completed your current programme of study, then you can still apply and you can provide your Degree Certificate at a later date.
- Degree Transcript
- a full transcript showing all the subjects you studied and the marks you have achieved in your degree(s) (original & official English translation)
- Personal Statement
- a detailed personal statement explaining your motivation for this particular programme
Careers
Graduates of the MSc in Planetary and Data Sciences will be equipped for a wide range of careers at the intersection of space, environmental science, and data analytics. Typical destinations include roles in space agencies, satellite and Earth-observation companies, environmental and climate services, government agencies, research institutes and the broader tech and data-science sectors.
The programme develops a combination of skills that employers actively seek:
- The ability to work with large and complex datasets,
- Strong quantitative and programming skills,
- Experience with remote sensing and geospatial data, and
- The capacity to turn technical analysis into clear recommendations for decision-makers.
You will also gain experience with modern tools and workflows used in industry, including data science, machine learning, and collaborative project work.
Depending on your focus, you may progress towards roles such as data scientist, planetary or space-data analyst, remote-sensing or GIS specialist, environmental data analyst, scientific programmer or research assistant in universities and research labs. The substantial research project provides an excellent platform for advancing to PhD study in planetary science, astroinformatics, geoscience, climate science, or applied data science.
Throughout the degree, you will have opportunities to strengthen your professional profile through project work, communication and presentation tasks, and exposure to real-world datasets and case studies – all of which provide strong preparation for competitive international job markets.
Our Experts
Teaching on the MSc Planetary and Data Sciences is delivered by experts in planetary science, data science and geospatial analytics. You will learn from researchers involved in major space missions, cryosphere and climate research, complex systems modelling and AI-driven data analysis across science and industry.
- Other Experts
- Professor M Carmen Romano
- Dr Lydia Sam
- Dr Thasshwin Mathanlal
- Dr Alex Brasier
- Professor Marco Thiel
- Dr Anshuman Bhardwaj
- Dr Miracle Israel Nazarious
- Dr Francisco Pérez-Reche
Information About Staff Changes
You will be taught by a range of experts including professors, lecturers, teaching fellows and postgraduate tutors. However, these may be subject to change - see our Student Terms and Conditions page.
Get in Touch
Contact Details
- Address
-
Student Recruitment & Admissions
University of Aberdeen
University Office
Regent Walk
Aberdeen
AB24 3FX