Course teacher(s)
Jean-François RASKIN (Coordinator)ECTS credits
20
Language(s) of instruction
english, french
Course content
Objectives (and/or specific learning outcomes)
The master thesis is a final work that comes at the end of the master study cycle which gives the student the opportunity to apply the skills that he/she has acquired during the MA. It is also an initiation to research.
The student chooses a subject proposed by a thesis director (this will be done in whole or in part during MEMO-F-403). Then, the student identifies, under the guidance of the thesis director, one or more questions or open problems related to this subject.
To answer the questions asked or solve the problems that were identified, the student undertakes a study of the state of the art based on bibliographical and exploratory research in order to shed rigorous and innovative light on the precise questions or problems that have been defined.
The thesis will therefore naturally include the following elements (the titles of the sections are not mandatory, and other sections can be introduced if need be, but those elements are expected content-wise):
1. A Section about the State of the Art, which is a synthesis of the scientific literature that reports on the state of the art in the subject addressed. This state of the art must be supported by the bibliography. At the end of the section, the reader must have a clear idea of the state of the art on the subject addressed, and must understand that the contribution of the master’s thesis is meaningful.
2. A preliminary section that defines clearly and precisely the subject being addressed and contains all the formal background necessary to understand the content of the master’s thesis. This section should use all the necessary scientific and mathematical rigour that the subject is calling for.
3. A detailed and rigorous presentation of the method followed to provide original answers to the questions or problems posed.
4. A rigorous exposition of the new solutions brought to the problem(s).
The objective of the dissertation is therefore to bring students at the end of their master's degree to deal with a subject of their choice while respecting the approach and scientific methods that were taught to them during their Master's training. It will also be necessary to ensure that the solutions adopted will have been chosen by displaying appropriate critical thinking skills.
Prerequisites and Corequisites
Required and Corequired knowledge and skills
The master thesis follows the course "preparatory works for the master thesis". The purpose of the preparatory work for the thesis is to have the students ready to start their research in the master thesis on the topic suggested by the promoter. This means that they need to have collected and understood the state-of-the-art, have potentially played with the basic tools they will need to initiate the research and have a clear understanding of the questions they wish to answer with their master thesis. All this needs to be clearly reported in in the preparation document and approved by the promoter before the next step can be taken.
Required and corequired courses
Teaching methods and learning activities
-The master thesis will be submitted in the form of a text, the length of which cannot exceed 100 A4 pages. Although there is no strict lower limit on the number of pages, the written text should be substantial and the length of a master thesis text is usually over 80 pages. The thesis will be written either in English or in French.
-The candidate must have the explicit agreement of his/her promoter to submit the thesis and the agreement of the adviser should only be given if the adviser judges that the work has enough qualities so that it is expected to convince the jury. If this agreement cannot be obtained, and if the student still wishes to defend his/her thesis, the jury will be officially informed of this fact by the secretary office before the defence.
-The defence of the dissertation work will be organized during an oral defence. During this oral defence, the candidate will present his work for 20 minutes, emphasizing its original aspects.
A question and answer session will follow the presentation of the work. During this session, the jury might question the candidate about the following topics (among others) :
1. A justification of the choice of works cited in the « state of the art » section. The candidate must thus have a clear idea of the content of the works cited and be able to explain how they are related to his/her own work.
2. Detailed explanations of the theoretical background of the work presented in the master’s thesis. The student must be able to explain, as a scientific expert, the algorithms, theorems, results,... at work in his/her master’s thesis.
3. The actual results (methods, experiments, and so forth) presented in the master’s thesis.
Following these questions, the jury will deliberate on the final grade.
Contribution to the teaching profile
-The use of generative AI is governed by « Article 40 » of ULB’s « règlement général des études ».
-Summary of the rules in Article 40 (please refer to the original text for completeness):
1. Generative AI cannot replace personal reflection and research (including consultation of primary sources).
2. Transparency: the student must be able to explain and justify the use of generative AI and indicate which contents were generated.
3. Compliance with copyright, plagiarism rules, and data protection is required.
These principles will be evaluated during the oral presentations/defenses of the preparatory work and the master thesis. Non-compliance will result in a grade strictly below 10/20. If fraud is detected (failing to apply the principles and trying to hide it), the grade will be 0/20.
Additional requirement for this thesis and its preparatory work
Include in both the « preparatory report » and the « final thesis » a section that « explicitly explains how generative AI was used » (e.g., rephrasing only; coding; generating artificial data; etc.). Every use must be detailed.
Further guidelines
-Substantial AI-generated text is often easy to identify by a careful reader and a domain expert, and such parts will be specifically questioned if there is suspicion about their origin.
-It is not acceptable to ask generative AI to produce the « state of the art » or a « bibliography summary », as producing these is part of the learning process for the thesis and its preparatory work.
-Any definition, model, algorithm, or explanation of an algorithm must be written by you (not generated by AI) or referenced as coming from the literature, and in both cases you must be able to fully explain them if they appear in your text.
-If the AI generate a text and this text contains plagiarism, then you are fully responsible for it.
Other information
Additional information
Additional Informations:
a) Jury Composition
Your jury must consist of at least your promoter (the professor supervising your work) and two other professors who teach courses in the Bachelor or Master programs in computer sciences. The promoter must be a faculty member of the Master's degree program in computer sciences. The composition of your jury should be submitted via email to maryka.peetroons@ulb.be no later than May 1st, 2026.
b) For a June 2026 submission
You must submit your master thesis via email to maryka.peetroons@ulb.be by end of May (precise dates will be sent to students)
c) For a September 2026 submission
You must submit your master thesis via email to maryka.peetroons@ulb.be by mid August (precise dates will be sent to students)
Campus
Plaine
Evaluation
Method(s) of evaluation
- Other
Other
The following criteria will be used for the evaluation. Those criteria apply to both the form and the content of the work.
About the content of the work:
- Background and motivation: does the student properly motivate his contribution, linking it to the state of the art? Is the bibliography adequate?
- Scientific rigour: does the student introduce the problem he/she addresses in a rigorous and comprehensive fashion, using proper rigour and mathematics if need be? Can he/she demonstrate (in the text and during the oral presentation) a deep and rigorous understanding of the background and of the results they present?
- Originality of the work : is the presented work original, and does it represent a meaningful contribution to the field? Could it lead to a scientific publication (this is not mandatory, but the best works would satisfy this criteria)?
About the form of the work:
- Quality of the text: is the text properly written, with proper spelling and grammar, proper use of mathematical notations, an adequate structure and a clean and attractive presentation?
- Quality of the oral presentation : did the the student deliver a convincing oral presentation, where he/she spoke eloquently ? Were the slides readable and well-structured ? Did the presentation summarise the contribution adequately?
fLanguage(s) of evaluation
- english
- french