Project Requirements

This page is dedicated to listing the particular project requirements for our MSc students.


MSc Information Studies: Data Science track and Information Systems track

MSc Software Engineering

MSc Computational Science

MSc Logic

Each program has very unique project requirements, ranging from duration to research fields.

MSc Information Studies 

Data Science Track and Information Systems Track

When creating your project proposals, please ensure that they adhere to the MSc Information Studies thesis requirements below.

The MSc Information Studies has two tracks, namely Data Science (DS) and Information Systems (IS). Both investigate the use of particular technology with respect to the origination, collection, classification, analysis, sensemaking, manipulation, storage, retrieval and dissemination of information.

In this context, students in the DS track focus on data, related structures and their algorithmic processing, for the generation of information, and the maintenance of data and information, mainly using machine learning approaches.

Students in the IS track focus on cognitive and social implications for the structures within and the use of information systems. Here the relation between data, information and knowledge is investigated on a systems level, including the design of datasets, interaction environments and underlying system architectures.

The focus of the thesis research will be the scientific study of a problem-oriented toward actual research themes in academia and society. The thesis project provides students with first-hand experience in working with established scientists or industry experts for a prolonged period of time.

The learning objectives of the research project comprise, that after completion of the thesis project, the student:

-is able to formulate a clear research question in the field of information studies and design a plan to answer that question

-can show state‐of‐the‐art knowledge in the area of the research project based on the relevant literature by applying in a practical situation

-is able to process the research data and to critically judge the obtained results in relation to the goals and the line of research of which the research project is part

-is able to describe and critically discuss the above activities in a written report, in which the methodology is accounted for and the original phrasing is substantiated

-is able to present and discuss the results to a scientific and non-scientific audience

-is able to function in a professional environment.

The student has to have finished all courses from the 4 blocks of the programme.

The research project’s objective is to give the student an opportunity to acquire practical experience in quantitative and qualitative scientific research methods and to learn to work independently.

The project requires an implementation that can be validated.

A master thesis is defined as “an individually written record of the student’s performed original research or design of a scientific nature”. It is an original, independent piece of work especially composed for this occasion containing the creative ideas of the student. Claims, hypotheses, policy recommendations and design choices need to be supported with arguments based on existing theory or empirical evidence.

The master thesis cannot consist of copied resources (internet, books, and journals), unless properly quoted, and the material has not already been submitted elsewhere (other courses, study programmes, universities) with the aim to receive study credits for this. The master thesis can, however, elaborate on previously submitted work, as long as it is clear which contribution of the student has been submitted for which study programme component.

As the program is interdisciplinary the students have a broad variety of domains they are knowledgeable in.

-Machine Learning


-Media analysis

-data analytics


-Efficient Image Similarity Clustering within Apple Orchards on Edge Devices

-Echocardiographic Clustering by Machine Learning in Children with Early Surgically Corrected Congenital Heart Disease

-End-to-End Learning on Multi-Edge Graphs with Graph Convolutional Networks

-Improving the Precision of the HyperLogLog Algorithm by Introducing a Bias

-A Business Value Perspective on Metadata Management

-A Requirements-Driven Redesign of a Terminology Maintenance Process in the Netherlands

-Carsharing: panacea or everlasting promise: Simulating the effect of car sharing policies on the modal split in Amsterdam

The students have good analytical skills regarding problem identification. They can identify potential solutions to the problem and then find in this solution space the answer that best addresses the problem.

The student has addressed a feasible problem through a research question that can be answered through quantitative or qualitative methods. As the project time is fixed to 3 months the problem cannot be complex and might address a smaller problem (i.e. the comparison of two machine learning approaches to identify the applicability of one as superior.).

Compensation is not required. This can be discussed individually with the student

The project runs in two parts – a 3-month thesis design (part-time) and a 3-month project (full-time). The usual start date of the actual thesis project is the 1st of April to the 30th of June).

MSc Software Engineering 

When creating your project proposals, please ensure that they adhere to the MSc Software Engineering thesis requirements below.

We work a lot of time on co-designing the research proposals. We do not expect companies to be able to formulate scientific research questions, but we always find very interesting scientific research problems that could be solved by our students and the solutions validated in the context of these companies. So, for SE, the companies are lab-like environments where our students conduct real-life experiments. This is extremely valuable and makes our program attractive and high standard. This means however a lot of work in the weeks after the Thesis Fair when the thesis coordinator sits down with students and helps them identify the research gap in these industry projects.

Of course, this is mostly not the case with projects proposed by our former students that are now working in various companies. They already know what we look for in a project and how to formulate scientific research questions.

The student should aim to master the scientific research process.

The project requires scientific research contributions. The project should be a mix of theory and practice.

Software engineering

Software testing

Software evolution

Model-based design


Requirements engineering

Software process


Programming languages

Cybe-physical systems




Data engineering

Measuring the degree of library dependency (available at:

The students from MSc SE are quite heterogenous: different countries, and different previous education; one thing they have in common: software is their second nature.

Ideally, publishable research, at least at a workshop level.

1 month thesis proposal, 3-5 months thesis implementation.

Compensation is not required. This can be discussed individually with the student.

MSc Computational Science

When creating your project proposals, please ensure that they adhere to the MSc Computational Science thesis requirements below.

The thesis aims to enable the student to develop more in-depth knowledge, understanding, capabilities, and attitudes in the study programme. A Master of Computational Science thesis should emphasize the scientific and modelling (computational ) aspects of the specific system under investigation. The thesis’s overall goal is to display the knowledge and capability required for independent work as a computational scientist.

Computational models are intended to implement causal processes in a single mechanism, which sets them apart from traditional data analysis techniques (such as machine learning) which are applied directly to available data. Without incorporating the same causal mechanisms either explicitly or implicitly (on which research indeed is taking place), in general, data analysis should be restricted to make inferences or predictions ‘within the data (e.g., clustering, regression, interpolation) or perhaps ‘near extrapolation’ (hypothetical scenarios which are still close to that of the data). The outcome of ‘far extrapolation’, however, requires incorporating the relevant causal processes (since their validity extends beyond any data set), which is by definition the goal of computational modelling.

This distinction can also be seen by comparing the ‘inductive capability’ of the learning algorithms (from past data, one can identify patterns) with the deductive capability of computational (mechanistic) models.

The graduate in Computational Science has a thorough knowledge of modelling and simulation of complex systems, computational methods and techniques, and the application of computational methodologies in application fields (ranging from e.g. physics or biology to medical sciences or engineered systems to complex social systems).

The computational science thesis should include one or more of the following broad aspects:

(i) developing computational models, that implement causal mechanisms to understand and predict the behaviour of any system. This could be any system such as social, technical, engineered, biological, physical etc. or

(ii) computational or mathematical techniques to analyze the behaviour of such models. These include strategies for sensitivity analysis, calibration and validation of models. or

(iii) developing computing techniques (e.g. distributed algorithms) to enable large scale, computational models.

-Theory of complex systems

-Urban complexity

-Computational Biology

-Computational Finance

-Theory of complex systems

-Urban complexity

-Computational Biology

-Computational Finance

The programme is oriented to prepare students for entry into a PhD programme in Computational Science or related disciplines, or into research positions outside academia. This is mainly triggered by the strong need in science and society for computationally trained researchers, in academia, industry and business.

A number of core and constrained courses (in the first year) help develop students with an independent and scientific mindset.

1) A CLS student is an expert in modelling and simulation as the third pillar of science and is capable of applying abstract models to understand societal questions. Courses such as Agent-Based Modelling and Complex System Simulation (in addition to teaching knowledge and skills) ask students to develop their own research questions and models by themselves on a diverse set of topics.

2) Students can apply models to Implement and study interventions and what-if scenarios to improve/optimize with respect to a practical application.

3) The student has basic knowledge about different techniques for modelling biochemical reactions, metabolic pathways, regulatory networks and cells (Boolean networks, coupled with ordinary differential equations, examples of partial differential equations, optimization techniques, and cell-based models).

4) Students obtain insight into distributed algorithms – concurrency concepts and are offered a bird’s-eye view of a wide range of algorithms for basic and important challenges in distributed systems.

The projects are not limited to any systems and context as long as they adhere to the requirements.

The research should be independent, but conducted under the daily supervision of (one or more) staff member(s) and embedded in a scientific project of the host institute, and should aim at a scientific publication in a conference or peer-reviewed journal.

The Master thesis (42EC) should include an extensive literature survey (accounting for 6EC) that will normally commence during Block 2 of Year 2.

From Block 3 Year 2 a student on the normal schedule will then spend full time on the graduation research (a remaining 36EC).

The final scheduling should be discussed with the supervisor of the graduation thesis and typically lasts 7 months.

Compensation is not required. This can be discussed individually with the student.

MSc Logic

When creating your project proposals, please ensure that they adhere to the MSc Logic thesis requirements below.

The thesis is a report on a substantial piece of scientific work, usually including a significant amount of original research that clearly demonstrates the student’s capacity to independently conduct research in an interdisciplinary environment.

30EC of work, including the writing of the thesis.

-Theoretical sciences such as:

-Theoretical Computer Science

-Theoretical Linguistics



-Communicate and Vote: Collective Truth-tracking in Networks

-The Classicality of Epistemic Multilateral Logic

-A Compositional Analysis of Dependence Statements

-Hyperintensional Logics for Evidence, Knowledge and Belief

-Algebraic models of type theory

Mainly formal-theoretical research skills, background in the theoretical sciences like, e.g., Theoretical Computer Science, Theoretical Linguistics, Mathematics and Philosophy.

Depends on the project.

The whole thesis amounts to roughly 5 months of work.

Compensation is not required. This can be discussed individually with the student.