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Astronomy and Data Science

Master

Structure of the programme

This 2-year programme focuses on the big-data aspects of both astronomy as a data-rich science and computer science. It prepares as much for a career in astronomy as in computer science, for careers in research as well as outside research, in academia or elsewhere in society. It consists of advanced Astronomy courses, two research projects in Astronomy, and selected courses from the Computer Science master's programme. Students wanting to follow this specialisation must be proficient in programming, in particular in the Python language.

Programme (120 EC)

Level EC
Electives
Astronomy Core Courses, at least 500 18
Instrumentation-related Astronomy Courses, at least 400-500 6
Astronomy Courses of any type 400-500 12
Mandatory Computer Science Courses
Databases and Data Mining 500 6
Advances in Data Mining 500 6
Neural Networks 500 6
Reinforcement Learning 500 6
Research Projects
First Research Project 500 30
Master's Research Project 600 30

Master Study Plan

At the start of the master’s programme, students are required to draw up the Master Study Plan: a complete list of planned courses and projects for two subsequent academic years in consultation with the Study Advisor Astronomy. To select courses, consult the course list for academic year 2017-2018 (see below) and the preliminary course list for academic year 2018-2019.

Learn more

For more information on the specific requirements of this specialisation, see the appendix of the Course and Examination Regulations.

Courses 2017-2018

Vak EC Semester 1 Semester 2

Astronomy Core Courses
Origin and Evolution of the Universe 6
Galaxies: structure, dynamics and evolution 6
Interstellar Medium 6

Instrumentation-related Astronomy Courses
Astronomical Telescopes and Instruments 6
Astronomy from Space 3
Detection of Light a 3
Detection of Light a + b 6
Project Management for Scientists 3

General Astronomy Courses
Computational Astrophysics 6
Large Scale Structure and Galaxy Formation 6
Star and Planet Formation 6

Specialist Astronomy Courses
Astrochemistry 3
Compact Objects and Accretion 3
Databases and Data Mining in Astronomy 3
Deep Learning 3

Mandatory Computer Science Courses
Advances in Data Mining 6
Databases and Data Mining 6
Neural Networks 6
Reinforcement Learning 6

Inter-faculty Electives
Science and the public: contemporary and historical perspectives 6
Science Methodology (SCM) 4

Career Orientation

Career orientation
During the Astronomy master’s education programme, we support you in making choices that are relevant to your future career. You will be stimulated to think about your ambitions and potential and to reflect on how to reach your goals. By actively exploring the possibilities, you enable yourself to make motivated study and career choices.

We organise various activities to help you think about questions like:

  • What are my strong skills and what skills can I still learn?

  • In which subjects do I want to specialise?

  • What subject will I choose for my Master Research Project?

  • Which electives fit my future ambitions?

  • Which type of job would I like to do after my Astronomy master’s?

  • What kind of employer would I like to work for?

Events Click here for the Astronomy career event calendar. This calendar contains an up-to-date overview of all career events relevant to Astronomy master’s students, including:

LU Career Zone
The Leiden University Career Zone is a website that offers support to Leiden University students and alumni, both during their studies and career. It offers advice, information and tools, including professional tests to draft your personal profile and job aplication tips.

Soft skills
In the Astronomy course descriptions in this e-Prospectus, behaviour-oriented skills are listed for each course. Although these soft skills cannot be measured like course objectives, being aware of the skills you acquire is important. They determine how you approach your work and your life and are therefore highly relevant to shaping your study path and future career.The soft skills you will come across in the Astronomy course descriptions include:

  • Problem solving - recognizing and analyzing problems, solution-oriented thinking

  • Analytical skills - analytical thinking, abstraction, evidence

  • Structured thinking - structure, modulated thinking, computational thinking, programming

  • Complex ICT-skills - data analysis, programming, simulations, complex ICT applications

  • Project management - planning, scope, boundaries, result-orientation

  • Responsibility - ownership, self-discipline, bear mistakes, accountability

  • Motivation - commitment, pro-active attitude, initiative

  • Self-regulation - independence, self-esteem, aware of own goals, motives and capacities

  • Verbal communication - presenting, speaking, listening

  • Written communication - writing skills, reporting, summarizing

  • Collaboration - teamwork, group support, loyalty, attendance

  • Flexibility - adaptability, dealing with change, teachability, eagerness to learn

  • Critical thinking - asking questions, checking assumptions

  • Creative thinking - resourcefulness, curiosity, thinking out of the box

  • Integrity - honesty, moral, ethics, personal values

Contact
Questions about your study and/or career path? Make an appointment with the Astronomy Study Advisor.