Internships

Currently available


TitleTypeSupervisor
Segmentation of microscopy images using deep learningTheoretical (Bachelor or Master)Philipp Savakis
p.e.savakis@vu.nl
Under dynamic conditions (changes in nutrient availability, ion concentrations, toxic compounds etc.), individual cells within a population show different responses. In order to quantify these responses, we aim to use a combination of microfluidics, phase contrast, and fluorescence microscopy. Images taken with the microscope need to be pre-processed for further analysis: the analysis algorithm needs to know in which part of the image the cells are located and what their shape is. So, in the first part of the data analysis, we need to solve a pixel-wise classification problem. The project focuses on implementing deep learning techniques (convolutional neural networks in caffe) to generate segmented images, which are then fed into a downstream processing pipeline. Proficiency in python and a general interest in deep learning techniques and pattern recognition are required, knowledge of Matlab/octave and caffe would be very helpful.
How does Lactococcus lactis respond to new conditions?
Experimental (Bachelor)Sieze Douwenga
s.douwenga@vu.nl
When a new environment occurs for an organism like L. lactis, different proteins, or metabolic states may be required to continue growth. This sometimes results in a lag-phase –observed for example when L. lactis is exposed to a sudden environmental transition from -80°C glycerol medium to fresh medium at 30°C. The relation between L. lactis response to sudden environmental transitions and various pre-culture conditions remains incomplete.
To uncover this relation we will study the response of L. lactis to around 100 environmental transitions, consisting mainly of transitions between various carbon sources and stress conditions. We will test transitions in parallel using 96 well or 384 well microplates and a plate-reader, which yields optical density growth curves. To extract the duration of the lag phase for each transition we will analyse the data with readily available scripts in python or R. This will shed light on the relation between various environmental transitions and the lag-phase exhibited by L. lactis.
Developing a protocol to grow yeast cells in water-in-oil emulsions, allowing for high-throughput mutant selections.Experimental (Bachelor)
Position filled
Rinke van Tatenhove
r.j.van.tatenhove-pel@vu.nl
Yeast cells are normally grown in suspension, where they all share the available substrate and where they have one shared extracellular space. However, sometimes we would like to look at the behavior of a cell independent from the surrounding cells. Think of cases where we want to select a mutant that produces more of a certain extracellular enzyme. Such a mutant cannot be selected in suspension, because all the secreted enzymes of all cells are in one shared extracellular space. Or think of the case where we want to select a mutant that has a lower growth rate, but produces more offspring. Such a mutant cannot be selected in suspension, because it will consume the shared substrate much slower than its fast growing neighbors. To select these kind of phenotypes water-in-oil emulsions can be used. In such an emulsion each cell has its own substrate pool and its own extracellular space. All these individual compartments can be analyzed and mutants can be sorted with a FACS, allowing for high-throughput mutant selection.
In this project you will develop a protocol to grow yeast cells in water-in-oil emulsions. You will design a medium with which we can make stable emulsions and in which yeast is able to obtain a high cell-density, to ensure growth of yeast in the small emulsion droplets. If this medium is successfully designed, we will apply the method to select yeast cells with a high biomass yield on glucose.
An EFM-based rationale behind FBA solutionsTheoretical (Bachelor or Master)Daan de Groot (d.h.de.groot@vu.nl) Eunice van Pelt (e.van.pelt-kleinjan@vu.nl)
In systems biology, Flux Balance Analysis (FBA) is commonly used to determine which reaction steps carry flux in a metabolic network. This provides insight in the biological activity of a cell in a specific condition. FBA is a linear programming problem and is therefore very computationally efficient, but it does not give information about the reason why some reactions are selected and others are not. To resolve this issue, we found a new way to interpret FBA in terms of Elementary Flux Modes (EFM) and the constraints that were hit by the network. An EFM is a minimal functional unit in which a metabolic network can be decomposed, i.e. EFMs are the minimal pathways that can produce biomass in steady-state. Each flux distribution is either a combination of EFMs or a single EFM. In this project we would like to investigate which and why certain EFMs are selected by FBA.

We expect that the optimal EFMs can be found by calculating the sensitivity of the optimal solutions to a small change in the input constraints (cap on uptake reactions). This could be the first step in a pipeline that needs to be developed (in Python) to visualize EFMs in a vector plot based on the FBA distribution. This will be tested and developed using a small toy model. Afterwards we will apply the pipeline on larger (genome-scale) metabolic models to study the choice of EFMs for specific conditions (e.g. growth on glucose, lactose, etc.). This would provide more insight in the number and quality of alternatives that a micro-organism has when regulating its metabolism.
How I wish I could measure phosphate in single cellsExperimental (Bachelor)Laura Guilherme Luzia
l.r.guilhermeluzia@vu.nl
Description: Pi is an important molecule in metabolism, signal transduction, enzyme regulation and a structural component of nucleic acids and cell membranes. In order to better understand how yeast central metabolism adapt and evolve in response to environmental changes, we want to quantify Pi levels in single cells. To do that, we will explore a FRET (Fluorescence Resonance Energy Transfer) sensor to measure the intracellular concentration of Pi under different carbon sources conditions in time-scale. Here, we want to characterize this ratiometric Pi sensor using kinetics assays and fluorescence spectrometry/microscopy techniques. In the end, we should be able to monitor Pi fluctuations in Saccharomyces cerevisiae in a range of conditions and to understand how free energy flows inside cells and is affected by external changes.
Optimize an industrial bacterial strain using genome scale modeling.Theoretical (Master)Douwe Molenaar
d.molenaar@vu.nl
At Corbion a genome scale model for one of their strains has been developed. They  would like to further explore this model and test different modeling tools, the ultimate goal being to optimize the strain performance. The tasks for this project are: 1) Testing of different tools for flux analysis and visualization (CBMPy-related but maybe also other tools). To understand the use of these models better, and to compare the performance and user-friendliness of different programs. 2) Using the modeling tools to predict defined targets for genetic engineering to improve fermentation performance. 3) Refining the genome scale model based on experimental data.

This internship will take place at Corbion in Gorinchem under supervision of Dr. B. Vriesendorp.
Biodegradation of novel pharmaceutical products.
Experimental (Master)Baptiste Poursat
B.A.J.Poursat@uva.nl
Organic pollutants, such as pharmaceutical and industrial products, are frequently detected in the environment, especially in aquatic habitats and in wastewater treatment plant (WWTP) discharges. They are considered as “emerging contaminants” since most of them are not currently covered by existing water-quality regulations, and their effects on the environment are still poorly understood. Knowledge on environmental persistency is essential to make an efficient environmental risk assessment of new manufactured chemicals. Indeed, a key component of both hazard determination and environmental risk assessment is the accurate estimation of the degradation of a chemical in the environment. Ready biodegradation tests (RBT) from the OECD guideline are required by the European REACH regulation to evaluate the biodegradability of chemical substances produced by industry. However, RBT suffer from several drawbacks related to the heterogeneity of their inoculum, due to their different origin and history. Indeed, the source, concentration and pretreatment of the inoculum are one of the most important factors that influence the RBT results and the extent of biodegradation of chemicals in the environment. The aim of this master thesis project is to compare the biodegradation rates of several pharmaceutical and industrial products (using LC-MS/MS) by different inocula from municipal, hospital and industrial WWTPs. Microbial communities will be characterized by Illumina sequencing and metagenomic analyses. Laboratory work for this project will mostly be performed in the laboratory of the University of Amsterdam (Science Park). For more information, please contact Baptiste Poursat, Dr John Parsons (UvA-ESS) or Dr Rob Van Spanning (VU Amsterdam).
Analysis of Lactobacillus crispatus genomes from healthy and pathological microbiomesTheoretical (Master)Douwe Molenaar
d.molenaar@vu.nl
Lactobacillus crispatus is a dominant organism in a healthy vaginal microbial flora. A pathological state of the vaginal flora is known as Bacterial Vaginosis (BV). The microbiome under BV is very diverse, and this state can cause several complaints and problems. The etiology of BV is unknown. Although L. crispatus is often present at low frequencies in the BV vaginal microbiome, it apparently can not become dominant in the population, as in a healthy microbiome. A possible explanation would be that L. crispatus in BV microbiomes differs genetically from L. crispatus in healthy vaginal microbiomes. To find support for this hypothesis you will reconstruct and compare genomic sequences of L. crispatus strains isolated from healthy and BV microbiomes. Researchers at GGD Amsterdam and TNO Zeist investigate phenotypic differences of the same strains. Your task will be to provide these researchers with supporting data and leads for investigation.

This internship is co-supervised by Prof. Remco Kort (TNO and VU).
S. pombe as an alternative model for eukaryotic central metabolismExperimental (Master)
Position filled
Johan van Heerden
j.van.heerden@vu.nl
Background
The two distantly related yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, have been instrumental in our current understanding of the eukaryotic cell and its processes. Much of what we know about the cell cycle and its regulation was borne from pioneering studies with S. pombe, while S. cerevisiae has been a favourite workhorse in studies on eukaryotic metabolism (especially central carbon metabolism) and textbooks on this subject are therefore filled with insights derived from this organism.

While the cell-cycle field has embraced S. cerevisiae as a complementary eukaryotic model, researchers with a focus on metabolism have yet to harvest the potential insights to be gained from systematic (and comparative) studies of S. pombe metabolism. Today, the majority of research on S. pombe is still dedicated to unraveling cell cycle regulation and other cellular functions such as DNA repair, maintenance and aging, with very little fundamental research on the central metabolism of this yeast.

While there are many similarities between these two species, there are also several important differences including: cell morphology, the mode of cell division, the position of cell-size checkpoints during cell-cycle progression, the role of glucose sensors, the ability to respire ethanol, the presence of a glyoxylate cycle and differences in mitochondrial functions.

As many of the differences between these two species pertain to metabolic functions, a better understanding of the metabolic profile of S. pombe should serve to greatly expand our compendium of knowledge on eukaryotic metabolism, beyond that of S. cerevisiae and cancer cell lines.

The project
In this project you will lay down the foundation for metabolic studies that use S. pombe as an alternative to S. cerevisiae. You will perform both physiological and metabolic characterisations of S. pombe - in experimental settings that are typical for S. cerevisiae - in order to gain detailed descriptions of (1) growth kinetics, (2) cell size distributions and (3) profiles of intracellular pH and glycolytic intermediates, under different growth conditions. It is hoped that these results will serve to identify key differences, but also similarities, between these two species and that these insights will form a basis for future research.

Techniques
Batch and/or chemostat cultivations
Genetic transformations to express fluorescent reporter proteins
Enzymatic assays to determine intracellular metabolite concentrations
And, depending on the progress of the project, one or several of the following analytical techniques: HPLC, Coulter counter, Flow cytometry and Fluorescence spectroscopy, Fluorescent microscopy.

Duration of project: 5-9 months

Your CV: Ideally you will have an experimental background, with experience working in a microbiological setting.

Start date: February 2017 or later.
Sequencing data analysis for vaccination strategies against melanomaTheoretical (Master)Douwe Molenaar
d.molenaar@vu.nl
Background
In recent years a number of vaccination strategies against melanoma (skin cancer) were designed. One of these strategies is targeting immune cells in the skin, like dendritic cells (DC) or langerhans cells (LC). This is done with dendrimers or liposomes coupled to tumor antigens to boost the immune system against the tumor. The group of Molecular Cell Biology and Immunology at the VU University Medical Center specifically uses the c-type lectin receptors DC-sign or Langerin to target the DC or LC resident in the skin. The pathways that are stimulated by targeting the c-type lectin receptors are still largely unclear. Therefore, the DCs are stimulated with different types of dendrimers and the mRNA changes are measured using next generation RNA sequencing. This project concerns the analysis of these next generation sequencing data, to reveal the genes and pathways that are stimulated with different kinds of dendrimers.

Methods
For the analysis of the next generation sequencing data we are planning to use R and Galaxy. Therefore, we are planning to write and run R scripts like the package edgeR, followed by pathway analysis using, among others, GSEA software. Galaxy is supported by CTMM-TRAIT and is used for annotating, normalizing and analyzing next generation sequencing data.

Goals

  • To analyse sequencing data to reveal differences between DC that are or are not stimulated by different kinds of dendrimers

  • Writing R script to utilize among others the package edgeR

  • Visualize the data

  • Analyze differentially expressed pathways using GSEA.

  • To analyze the data using Galaxy


Your profile
You are a Bioinformatics/Systems Biology MSc student who is interested in analyzinglarge scale datasets to answer a biologically relevant questions. You are (able to quickly become) familiar with R and other programming languages, and you are interested in working in a multidisciplinary environment, surrounded by wet-lab biologists.

This internship will be co-supervised by Dr's Joyce Lubbers and Juan Garcia Vallejo of the Department of Molecular Cell Biology and Immunology, VU University Medical Center.
Linking microbial communities to crude oil weathering in mangrove environmentsExperimental (Master)Paul Iturbe Espinoza
p.iturbeespinoza@vu.nl
Shell uses land farming to clean up sites impacted by oil spills. Land farming reduces the concentration of petroleum constituents present in soils through processes associated with bioremediation. In sensitive ecosystems, such as mangroves, traditional remediation methodologies such as land farming can be particularly difficult due the soft ground conditions and sensitive nature of vegetation. In those types of environments, removal of surficial oil and gentle flushing of sediments to remove free oil can be effective in reducing oil concentrations. Any residual oil is further reduced by biodegradation to a level where mangrove vegetation can recover. The rate at which the biodegradation occurs is an important factor in the restoration of the mangrove ecosystem but relatively few data are available on this. Also, while it is widely acknowledged that microorganisms play an important role in the breakdown, linking rates to microbial community composition and other abiotic factors is very hard.

The objective of this MSc research project is to increase the understanding biodegradation processes in mangroves, both in terms of kinetics, involved micro-organisms and contributing abiotic factors. Shell can provide soil samples which will span a range of severity and type of oil contamination (fresh versus weathered) which can be used in experiments. It is envisaged that the student will develop a work plan based on a comprehensive literature study on this topic. Laboratory experiments can be used to establish laboratory estimates of the rate of biodegradation which can be combined with microbial community profiling as determined by Illumina amplicon sequencing.

The project is in collaboration with the Shell Technology Centre Amsterdam.
Impact of remedial agents on microbial communitiesExperimental (Master)Paul Iturbe Espinoza
p.iturbeespinoza@vu.nl
The IUCN-Niger Delta Panel (IUCN-NDP) was established at the request of Shell Petroleum Development Company of Nigeria Limited (SPDC), to provide science-based recommendations for the remediation and rehabilitation of biodiversity and habitats of oil spill sites in the Niger Delta. Land farming is widely used by SPDC to clear residual oil from spillages to soil in the Niger Delta. This approach reduces the concentration of petroleum constituents present in soils through processes associated with bioremediation. It is proposed by the IUCN that the use of bio surfactants, enzymes and sorbents can improve the effectiveness of this treatment. SPDC is planning to perform comparative pilot scale testing in Nigeria to determine the relative efficacy of the IUCN-NDP recommended remediation agents. It is anticipated that the tests will be performed in fully contained bio cells. The success of soil remediation by land farming is generally dependent on availability of nutrients and oxygen within the system plus the ability to overcome some of the mass transfer issues associated with hydrocarbon biodegradation. Consequently, the effects of oxygen, nutrients mass transfer will also be incorporated into the test plan in order to gain a better understanding of what influences efficient biodegradation in Nigeria soils. The experiment will test the effectiveness of the following factors on remediation success:

Nutrients (Agricultural Fertilizer), (Bio)surfactants, Enzyme products, Natural Sorbents, Tilling (oxygen and mass transfer)

The IUCN have commented that the success of remediation maybe dependent on the composition of the indigenous microbial community within the soil as determined by Illumina amplicon sequencing. Therefore, we would like to understand if and how microbial communities differ during treatment with various forms of remediation agent. The size and scope and specific objectives of the study can be discussed in more detail if you are interested developing a project. The project is in collaboration with the Shell Technology Centre Amsterdam.
The role of metabolic interactions in antibiotic toleranceTheoretical (Master)Bas Teusink
b.teusink@vu.nl
Bacteria in polymicrobial infections interact with each other. These interactions can change the environment to such an extent that some bacteria can become more or less susceptible to antibiotics. Metabolic interactions likely underlie this antibiotic tolerance effect. By means of metabolic modeling you will investigate some of these potential antibiotic-tolerance interactions in polymicrobial infections.

This internship is a cooperation with Dr Marjon de Vos from Wageningen University
The regulation of glycolytic-to-gluconeogenic transitions in different yeast speciesTheoretical/Experimental (Master)
Position filled
Phillipp Schmidt
p.schmidt@vu.nl
&
Johan van Heerden
j.van.heerden@vu.nl
The preferred mode of metabolism for most yeast species is glycolysis. This metabolic pathway breaks down glucose or other sugars and produces pyruvate, which can further be utilized in fermentation or respiration in order to produce energy and precursors for biosynthesis. When encountering excess levels of glucose, the baker’s yeast Saccharomyces cerevisiae performs aerobic fermentation, which leads to the formation of ethanol. This is also called the Crabtree effect. Upon depletion of glucose it can utilize the previously produced ethanol as carbon source. This metabolic transition is called the diauxic shift. In order to grow on ethanol, the cells need to synthesize glucose and other metabolic intermediates. This achieved through the gluconeogenic pathway, which is a essentially glycolysis operating in the reverse direction. Due to the irreversibility of two glycolytic reactions, new enzymes need to be expressed for this pathway including FBPase (Fructose 1,6-bisphosphatase). The regulation of this enzyme is not completely understood, even though it has been intensely studied in S. cerevisiae. For example, an open question remains regarding the specific signals that lead to induction of this gluconeogenic enzyme - are low glucose levels sufficient to signal activation of gluconeogenic enzymes, or does extracellular ethanol play a role?

To find answers to these questions, other yeast species may provide clues. For example, Schizosaccharomyces pombe, like S. cerevisiae, exhibits the crabtree effect, but cannot consume the ethanol it produces via aerobic fermentation. Does ethanol still play a role in inducing gluconeogenesis? There are also crabtree negative yeasts, like Kluyveromyces lactis, that do not produce ethanol from glucose in the presence of oxygen. Clearly, in this case ethanol cannot play a role in signaling glycolytic-to-gluconeogenic transitions.

In this project, we want to compare the dynamic regulation of glycolytic-to-gluconeogenic transitions in these three different yeast species. We will use a technique called RNA FISH to count single mRNA molecules for PFK (Phosphofructokinase, a glycolytic gene) and FBPase (a gluconeogenic gene) in individual cells as they transition from excess to no glucose. By comparing differences in the induction of FBPase between these yeast species, the aim is to gain a better understanding of the roles that glucose and ethanol concentrations respectively play in inducing gluconeogenesis.

Duration of project: 5-9 months

Your CV: Ideally you will have a strong experimental background, and some basic programming skills (e.g. Python, R, Matlab).

Start date: May 2017 or later.
Building a genome scale metabolic model for the fission yeast S. pombe Theoretical (Master)Johan van Heerden
j.van.heerden@vu.nl
&
Eunice van Pelt-Kleinjan
e.van.pelt-kleinjan@vu.nl
Background
The two distantly related yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, have been instrumental in our current understanding of the eukaryotic cell and its processes. Much of what we know about the cell cycle and its regulation was borne from pioneering studies with S. pombe, while S. cerevisiae has been a favourite workhorse in studies on eukaryotic metabolism (especially central carbon metabolism) and textbooks on this subject are therefore filled with insights derived from this organism.

While the cell-cycle field has embraced S. cerevisiae as a complementary eukaryotic model, researchers with a focus on metabolism have yet to harvest the potential insights to be gained from systematic (and comparative) studies of S. pombe metabolism. Today, the majority of research on S. pombe is still dedicated to unraveling cell cycle regulation and other cellular functions such as DNA repair, maintenance and aging, with very little fundamental research on the central metabolism of this yeast.

While there are many similarities between these two species, there are also several important differences including: cell morphology, the mode of cell division, the position of cell-size checkpoints during cell-cycle progression, the role of glucose sensors, the ability to respire ethanol, the presence of a glyoxylate cycle and differences in mitochondrial functions.

As many of the differences between these two species pertain to metabolic functions, a better understanding of the metabolic profile of S. pombe should serve to greatly expand our compendium of knowledge on eukaryotic metabolism, beyond that of S. cerevisiae and cancer cell lines.

Method
In this project you will build a new genome-scale metabolic model (GSMM) using software developed in our group, MetaDraft. This will enable the construction of a draft genome-scale model based only on a sequenced genome and a curated database of template models.

Outcome
You will use this GSMM model to predict the ability of S. pombe to produce biomass (i.e. to grow) on various carbon substrates. These predicitons can then be compared to existing and new experimental data, to improve and validate the model.

It is expected that this work will lead to a functional GSMM that will provide a valuable asset to the burgeoning field of S. pombe metabolic studies.

Duration of project: 5 months

Your CV: Ideally you will have a theoretical background and programming experience (preferably Python or Matlab).

Start date: May 2017 or later.
Genetic manipulations in S. Cerevisiae using CrispR/Cas9
Experimental (Bachelor)Rick Nijhout
r.m.nijhout@vu.nl
Genetic manipulations of the Fructose 2-6 Bisphosphate synthesis and degradation pathway will be performed in the W303 yeast strain. Subsequently you will perform phenotypical characterization of the mutants using the ratiometric pH sensor "Phluorin" in Flow Cytometry experiments.
Drug targeting in metabolism: from antiparasitic target to drug screening assaysExperimental (Master)
Position filled
Jurgen Haanstra
j.r.haanstra[at]vu.nl and Marijke Wagner
Trypanosoma brucei is the causative agent of deadly African Sleeping Sickness. In its lifestage inside the mammalian host this unicellular parasite relies almost exclusively on glycolysis to generate ATP. As 50% inhibition of glycolysis is sufficient to kill the parasite, glycolysis is a prominent target pathway for antiparasitic drugs. A network-based analysis has shown that the glucose transporter has the highest control over the glycolytic flux in T. brucei and is therefore a prominent drug target.
To get to a semi- to high throughput assay to test drugs against the T. brucei transporter we have complemented a yeast glucose-transporter null mutant with the trypanosome transporter. In this project you will design and test drug screening assays on live T. brucei and for the yeast complementation mutant.
If desired, this project can incorporate a modelling part as we have a kinetic model of T. brucei glycolysis (and yeast).
How does soluble adenylyl cyclase regulate the Warburg effect in liver cancer cells?Modelling (Master)Jurgen Haanstra
j.r.haanstra[at]vu.nl and Bas Teusink
It is generally established that most cancer cells have a different metabolic programming than primary tissue cells. In general, tumor cells perform “aerobic glycolysis” which means that they metabolize glucose by a high rate of glycolysis and subsequent fermentation into lactate, but with very limited further oxidative metabolism in the citric acid cycle. This phenomenon is called the Warburg effect. Although much research has been dedicated to the Warburg effect and several targets have been proposed, the overall mechanism remains poorly understood.
Colleagues at the AMC/Tijtgat institute have recently found that soluble adenylyl cyclase (sAC) plays an important regulatory role in the choice for aerobic glycolysis. Although sAC is the evolutionary most ancient adenylyl cyclase in mammals, it has been studied much less intensely than the transmembrane adenyl cyclases which are regulated by G-proteins. In contrast to these, sAC was found to be activated by HCO3- and also by its substrate ATP, which makes sAC an exquisite metabolic sensor.
Inhibition (or knockdown) of sAC in in several cancer cell lines enhances lactate formation and decreases oxidative glucose metabolism, thereby aggravating the Warburg effect. The exact target(s) of sAC in energy metabolism remain to be identified, but its activity affects glycolysis, the pentose phosphate pathway and glycogen homeostasis.
The goal of this project is to identify possible metabolic targets of sAC action in the human hepatoma cell line HepG2 cells. You will do this by using (and expanding) existing kinetic models of HepG2/ hepatocyte metabolism as well as core models of metabolism. With these models you will investigate whether and how metabolic regulation can explain the measured changes in metabolite concentrations after sAC inhibition (or knockdown).

Joined projects of Molecular Cell Biology and Earth Sciences for master students


For students not studying at the VU University Amsterdam

Internships are in principle open for students from other universities in the Netherlands or outside the Netherlands. We welcome for example ERASMUS students. Please note a few things:

  • We ask for a minimum stay of 4 months (3 months research, one month report writing) with a starting date outside the holiday season (July, August).
  • You have to be able to support your daily expenses (e.g. food, accommodation) and travelling to/from the Netherlands. Often, the international office at your own university can assist you in obtaining grants (e.g. ERASMUS grants). You may also check http://www.nuffic.nl/international-students/scholarships/grantfinder. Research costs will be covered by the internship project. We can help you with providing letters etc. for applications.
  • Finding accommodation in Amsterdam often takes 3 to 6 months. Erasmus students are helped via our international office in arranging accommodation in the VU hospitium in Amsterdam. Non-Erasmus students are advised to look for accommodation well in advance, in particular if you want to start in September, October or November.
  • Students from outside the EU should take into account that they may require a visa for the Netherlands, and that arranging this may also take a few months. Please check with the Dutch embassy in your country.
  • Non-Erasmus students may have to register at the faculty (this is relatively easy for students from other Dutch universities), or alternatively, require a statement of hospitability, and possibly have to pay a fee.

Please contact Dr. Rob van Spanning (rob.van.spanning@vu.nl) if you want to do an internship in our group, and indicate your preferred project(s), starting date, length of internship, and how you will support yourself (costs for food, accommodation), as we are unable to support you financially.