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Better Science for Computer Scientists - CANCELLED


Admission requirements

This course is recommended to second year Master Computer Science students and is also open to all PhD students of LIACS.


There are many skills a successful scientist needs to develop that go beyond technical capabilities and knowledge in their field. These include communicating research methods and results through presentations and publications; designing and conducting experiments, as well as analysing experimental results; designing, describing and carrying out research projects; assessing and supervising the work of others; dealing with failure; positioning themselves for success, honours and awards; networking; and many other skills that are usually acquired in an informal, unstructured fashion while working with a supervisor or in a research group.

In this course, I will share common practice related to these topics as well as experience and advice collected throughout my own career. Classes will be highly interactive, with at least 50% of our time spent on group activities designed to create deep understanding of the topics covered in the course, and to help students build the skills needed to become better scientists.

Course outline

Module 1: better talks

  • purpose of scientific talks

  • structure and mechanics

  • slide preparation, layout

  • handling questions

  • delivery, timing, managing nervousness

Module 2: better papers

  • paper writing (including collaborative writing, role of structure, outlining, stacked headings, spell checking; writer’s block)

  • publication process (workshops, conferences, journals; special issues)

  • choice of venue

  • paper reviewing (including peer review process, alternatives - arXiv, TRs, …; when to say no; benevolent sceptic)

  • self-publishing (including arXiv, TRs) - pros and cons

  • editorial work (incl pc chairing / discussion)

  • assessing impact

Module 3: better experiments

  • the scientific method (role of experiments)

  • exploration vs confirmation; incl statistical tests (emphasise resampling methods)

  • collecting data (and ensuring its preservation, incl. what to keep)

  • documenting protocols, results

  • parameter settings, meta-algorithmics

  • generic issues in coding, debugging; code preservation

  • reproducibility

Module 4: better projects

  • grant proposal writing (incl tenenbaum’s law, the pitch)

  • grant proposal reviewing

  • master and phd proposals + defence (incl external examiner; how to prepare)

  • working in a team (incl sharing/communication tools, effective meetings)

  • choosing projects to work on (incl when to say no)

Module 5: better science

  • scientific method (revisited)

  • hypotheses

  • dealing with failure

  • assessing impact (bibliometrics, h-index, …)

  • creating / amplifying impact

  • awards and honours

  • networking (incl. the role of conferences)

  • supervision and mentoring (choosing / working with a supervisor, mentor)

  • work/life balance

  • how to be successful as a MSc/PhD student/Scientist

Course objectives

The overall goal of the course is to help students acquire the meta-knowledge and develop the skills they need to do good (actually: better) science. This includes skills related to giving presentations, writing papers, conducting experiments, developing and carrying out projects as well as general skills that help them become productive and respected members of their scientific communities. These skills will be valuable for Master students and PhD candidates in computer science, but to a large degree are more broadly useful.


The most recent timetable can be found on the students' website.

Mode of instruction

Interactive seminar.

Total hours of study: 84 hrs. (= 3 EC)
Lectures: 26:00 hrs.
Practical work: 50:00 hrs.
Examination: 8:00 hrs.

Assessment method

Students will be assessed based on their in-class participation, including preparedness for in-class activities, and through a sizeable take-home exam.

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

Not applicable.


  • You have to sign up for courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.

  • LIACS PhD students can register for the course by sending an email to José Visser (Education Coordinator Master Computer Science).


Lecturer: Prof.dr. H.H. Hoos