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.
Module 1: better talks
purpose of scientific talks
structure and mechanics
slide preparation, layout
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)
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
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)
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)
how to be successful as a MSc/PhD student/Scientist
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 at the Computer Science (MSc) student website.
Mode of instruction
Total hours of study: 84 hrs. (= 3 EC)
Lectures: 26:00 hrs.
Practical work: 50:00 hrs.
Examination: 8:00 hrs.
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.
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 the Education Coordinator Master Computer Science.
Lecturer: Prof.dr. H.H. Hoos