Promotor: Roeland M.H. Merks

Epithelial-mesenchymal plasticity (EMP) and tumor cell migration play an important role in cancer progression, and an improved understanding of the mechanisms underlying these concepts is essential for developing new targeted approaches.

Accelerating the diagnosis and personalising the management of inherited metabolic diseases.

Science, Leiden Institute of Chemistry (LIC)

There is a need for alternative methods to replace, reduce and refine (3R) animal experimentation. Combining experimental data from high-throughput in vitro studies with in silico modeling is a promising approach to unravel the effect of chemicals on living cells and to gain a better understanding of…

Promotor: Prof.dr. J.N. Kok

In this project, we aim to obtain a quantitative understanding of the role of the immune system in tumor regression, of the role of tumor cell heterogeneity in cancer growth and of tumor cell migration properties.

An integrated approach of physiological concepts, advanced statistical approaches and large clinical datasets.

In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.

Drug-target binding kinetics determine the time course of the central event in pharmacotherapy: Drug-target interaction.

Nonparametric Bayes for high-dimensional models: contraction, credible sets, computations

Computational linguistics uses computational methods to help answer linguistics questions across a variety of topics.

Projects within the theme ‘Computational Biology’ aim to employ mathematical or computational dynamical modelling approaches to discover novel concepts that are important for drug development.

Promotor: Prof.dr. E. Deprettere

We investigate reaction systems, a novel computational model gleaned from the biochemical reactions taking place in living cells and information processing in nature.

This thesis focuses on two processes involved in fighting infections: metabolism and immune cell motility and navigation.

The goal of the MODOMA-project is to create a computer model of language acquisition.

The master's specialisation Bioinformatics at Leiden University focuses on research, development and application of computational tools and approaches for expanding the use of biological, medical, behavioral and health data.

Immunotherapies for cancer are an emerging class of therapeutic strategies which aim to treat cancer via augmentation of the immune system.

Research in the natural computing group covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.

A complex community of microbes develops in the infant gut shortly after birth. We call this community the infant gut microbiota. The microbiota influences the health of the infant, which makes the composition and function of the infant gut microbiota an important topic to study.

The Computer Systems, Imagery & media (CSI) research programme performs research on methods and techniques for the design, implementation and application of advanced computer systems, in particular parallel, distributed and embedded computer systems.

This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.

In this research group, led by Dr. Joost Beltman, the aim is to employ mathematical and computational dynamical modelling approaches in order to quantitatively and mechanistically understand the dynamical behaviour and regulation of intracellular networks of genes, proteins and metabolites as well as…

The aim of this thesis is to present novel techniques for proving cryptographic schemes secure against quantum adversaries. Most results are within the context of an idealized model called the ‘quantum random-oracle model’.

Research in the natural computing cluster covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.

We strive to address the challenge of constructing a modeling language to write software which can take advantage of recent hardware developments (multicore, cloud) without compromising in its abstraction levels.

Can the (industrial) herbal extraction process be mathematically described and can this model be used to optimize the extraction in terms of quality and economical parameters?

Promotor: Prof.dr. S. Haring

We see computer programming as an essential skill. It enables you to be self-sufficient in building tools, processing data, visualizing research output, communicating research results, etc. Moreover, it empowers you to make beautiful things.

In this theme you will be supplied with a firm background in the core of current computational linguistics and a solid comprehension of its neighboring fields.

In this project we study the properties of statistical- and rule-learning mechanisms in relation to the acquisition and evolution of language. We ask to what extent these mechanisms are unique to humans - or to human language - by comparing the acquisition of vocal structure in two species: humans (infants)…

This dissertation focused on computational methods based on first principles calculations using the Density Functional Theory (DFT) framework. Emphasis was laid on affordable methods that can provide a tradeoff between computational expense and accuracy.

The zebrafish is a promising vertebrate model organism in early drug discovery and development.

Computational thinking, programming, and algorithms form the basic of many of the things that are shaping our world, the way we work, interact, organize ourselves, and even spend our free time with social networks, streaming media, and games. And this transformation is far from being complete, it is…

This dissertation investigates Extended Lexical Units (ELUs), elements that are bigger than just one word and which are stored in the Lexicon.

Describe and identify what dosimetry parameters are of importance to interpret dose-response relationships (eg., mortality, sub-lethal, growth or reproduction inhabitation, DNA damage and reactive oxygen species, etc. ) for metal-based nanoparticles? How to develop quantitative models that enable to…

LIACS is partner in the project 'Stereotyping in Computer Science.' The project is a collaboration between multiple universities and the Dutch national expert organization on girls/women and science/technology (VHTO), which will investigate the stereotypes that children hold about computer scientist…

Are you thinking about studying Computer Science? Learn more and watch the videos. Note: As of September 2025 you can also combine this master programme with the Business Studies specialisation.

PhD candidates carry out a programme of independent research and additional (limited) course work, culminating in production of a PhD thesis in typically 4 years.

Research in this group, headed by Gerard van Westen, focusses on computational methods integrated in different parts of the drug discovery process. More specifically, topics include innovative treatments for cancer, selectivity modeling, translational research, allosteric modulation, drug resistance…

This dissertation is concerned with the development of grammar. Starting from a usage-based perspective, which holds that children use domain-general learning mechanisms to acquire the grammatical patterns of their mother tongue, Beekhuizen shows how to operationalize various concepts from this tradition…

In this work we describe three methods to improve the performance of Quantum Field Theory calculations.

Beowulf clusters looking for new frontiers.

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

Matthijs van Leeuwen of the Leiden Institute of Advanced Computer Science develops methods to make computer models interactive. With interactive models, experts can combine information from raw data with their own knowledge to make predictions more accurate. 'In this way we hope to build models that…