PhD Monitor
/Detail
Data Science● OpenMastersPreview

Master of Science in Data Science

Interdisciplinary master’s programme combining statistics, computer science, and mathematics for data-driven problem-solving.

Best for:Best for graduates with a strong background in mathematics, statistics, or computer science seeking to specialise in data-driven problem-solving and interdisciplinary research.

University of Oslo · Oslo, Norway
More professors at University of Oslo
Statistics and Machine LearningDatabase Integration and Semantic WebData Science and Life ScienceLanguage TechnologyDigital Image Processing
This is a masters position — not a PhD studentship.
Deadline
—
Funding
—
2 years
Start date
Flexible (typically autumn semester)
Location
Oslo
Norway

Overview

The Master of Science in Data Science at the University of Oslo equips students with the skills to extract meaningful insights from vast and diverse datasets. This two-year programme integrates core areas such as probability theory, machine learning, algorithms, and database management, preparing graduates to tackle real-world challenges in sectors like medicine, finance, and environmental science. Students engage in hands-on projects, often linked to industry and public sector collaborations, and can specialise in areas such as statistics, machine learning, or life sciences. The programme fosters both theoretical understanding and practical application, culminating in a master’s thesis addressing industry or research-based problems. Students also benefit from a vibrant academic community and opportunities for international exchange.

Data ScienceMachine LearningStatisticsComputer ScienceBig DataData AnalysisData VisualizationData Engineering

What you'll do

  • Develop a deep methodological understanding of data science principles, including probability theory, statistical inference, and machine learning algorithms.
  • Apply theoretical knowledge to practical challenges through hands-on projects and real-world datasets from industry, public sector, or scientific disciplines.
  • Conduct independent research and contribute to a master’s thesis addressing a specific problem in collaboration with academic or industry partners.
  • Engage in interdisciplinary learning by integrating knowledge from statistics, computer science, and general mathematics.
  • Participate in group projects and collaborative work, fostering teamwork and communication skills within a diverse academic community.
  • Utilise modern data collection techniques and tools to process and analyse large-scale datasets efficiently.

Requirements

Degree required: Bachelor's degree in a relevant field such as mathematics, statistics, computer science, or a related discipline.

Degree offered: Master of Science (MSc)

Language: English proficiency; no specific test score mentioned but typically expected for international applicants.

Instruction: English

Required skills
  • Strong foundation in mathematics, including probability theory and statistics.
  • Basic knowledge of computer science, including algorithms and programming.
  • Ability to work independently and collaboratively on research projects.
  • Familiarity with data collection, processing, and analysis techniques.
Nice to have
Experience with machine learning frameworks or tools (e.g., TensorFlow, PyTorch).Knowledge of database management systems (e.g., SQL, NoSQL).Background in data visualisation tools (e.g., Tableau, Matplotlib).Prior exposure to interdisciplinary research or industry collaborations.
Eligibility
  • Open to international applicants; no specific nationality restrictions mentioned.
  • No age restrictions or prior experience caps.

Funding & terms

Type
Unknown
Amount
—
Duration
2 years
Programme
—

Programme and admissions

Admissions not verified

A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.

Intake
Not confirmed by the source
Duration
Not confirmed by the source
Teaching language
Not confirmed by the source
Taught / research mode
Not confirmed by the source
Study mode
Not confirmed by the source
Campus
Not confirmed by the source
Prerequisites
Not confirmed by the source
Application instructions
Not confirmed by the source
Tuition
Not confirmed by the source
Funding
Not confirmed by the source

How to apply

Applicants must apply through the official University of Oslo application portal. The process involves submitting academic transcripts, a statement of purpose, and proof of English proficiency if applicable. A mandatory welcome meeting for new students is held at the start of the semester.

Documents required
  • CV or resume
  • Academic transcripts and degree certificates
  • Statement of purpose or research proposal
  • Proof of English proficiency (if required)
  • Letter of recommendation (number not specified)
↗Check programme and admissions

Contact

Lab
Centre for Research-based Innovation BigInsight and Sirius
University of Oslo
Norway
See the full position

Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.

No card · 10 free AI match scores
Explore this programme
Check admissions, intake and funding with the official source; a listing does not mean applications are open.