Undergraduates & Masters
The Centre for Genomic Regulation (CRG) aims to provide highly motivated undergraduate and master students the opportunity to conduct research at the CRG. The goal is to encourage students (from all nationalities) in the pursuit of a scientific career giving them the prospect to get experience in an international laboratory while improving their skills.
The CRG is a center of excellence with international teams representing a broad range of disciplines, with first class core technologies to support the research projects, a wide range of seminars given by high-profile invited speakers, and courses on complementary and transferable skills integrated with the training programme.
We accept applications throughout the year for any type of internship with a learning agreement with your university. Have a look at our labs and research programmes and contact the Group Leader of your choice directly with the following documents attached:
- Motivation letter
- CV
- Reference letter
- University transcripts
Acceptance will depend on the capacity of the research group and the ongoing projects.
We host online events and workshops to inform you about various opportunities available at the CRG and guide you on how to search for PhD positions. If you are keen to learn more, fill out this form HERE.
Below are some fellowships available for the academic year 2024/2025:
Evolutionary Processes Modeling
PROJECT DESCRIPTION - Evolutionary history modeling of cancer
Cancer / Natural Selec
tion / Evolution / Inference / Modeling
Cancer arises due to altered functions of proto-oncogenes and tumor suppressor genes which confer fitness advantages at the individual cell level that allow proliferation into populations of malignant cells. Disruption of function is commonly mediated by driver mutations in the implicated genes. However, mutagenesis is in itself a random process that also generates many passenger mutations that are inconsequential for cancer. The discovery of cancer drivers therefore depends on our ability to model the neutral probabilistic process of mutagenesis in order to identify out-of-distribution events that may be attributable to natural selection. In this project, we aim to improve and deploy a novel statistical method for cancer driver detection based on the evolutionary history of human tumors.
WHO ARE WE LOOKING FOR?
We are seeking a master’s student currently enrolled in a degree program related to bioinformatics, statistics, mathematics, physics, biology, genomics, life sciences, or engineering. The ideal candidate should have experience with basic programming and a solid foundation in statistical methods. A keen interest in working in a fully dry lab environment is essential, with opportunities to apply statistical techniques to genomic data, enhance software development capabilities, and strengthen data analysis and management skills.
If you are interested please apply by contacting the PI and Miguel Angel Cortes - HERE
Cellular & Systems Neurobiology
DIERSSEN Lab - AWARDED
PROJECT DESCRIPTION
Down Syndrome / Intellectu
al Disabilities / Gene Deregulation / Anatomical Alterations
Down syndrome (DS), resulting from full or partial trisomy of human chromosome 21 (Hsa21), is associated with various neurological alterations, including intellectual disability, Alzheimer's disease, epilepsy, and autism spectrum disorder. This chromosome triplication leads to complex gene deregulation, affecting both triplicated and non-triplicated genes, making it challenging to investigate the underlying mechanisms behind the DS neurological phenotype. One common strategy for studying these mechanisms has focused on characterizing the phenotype of animal models with an extra copy of a single DS triplicated gene, such as DYRK1A, DSCAM, KCNJ6, or APP; as well as trisomic models where the triplication of one gene has been corrected. However, less attention has been given to exploring the direct impact of deregulated non-triplicated genes in the DS neurological phenotype, particularly those that are underexpressed.
In this project, we investigate one of these underexpressed genes. Our preliminary data from a DS mouse model shows a reduced number of neurons expressing this gene, a finding consistent with two independent RNA-seq studies of DS human brains that also report decreased gene expression. Furthermore, in knockout models for this gene, the hippocampal synaptic plasticity is impaired due to excessive inhibition, a phenomenon also observed in DS mouse models. This excessive inhibition has been proposed as a key contributor to DS-related intellectual disabilities, known as the over-inhibition hypothesis. These findings have driven us to further investigate the impact of this underexpressed gene in DS neurological alterations and assess its potential as a therapeutic target.
WHO ARE WE LOOKING FOR?
The student ideally should have a strong interest in neuroscience and either a biology background with a willingness to learn quantitative methods or a background in computer science, engineering, or physics with a willingness to learn biological techniques. The student should be independent, persistent, proactive, and well-organized. The project involves hands-on implementation of laboratory techniques, including PCR, brain slicing, fluorescent immunohistochemistry, western blotting, and confocal imaging, as well as the application of quantitative methods such as image and statistical analysis pipelines. Prior experience in these areas is not mandatory but would be advantageous.
If you are interested please apply by contacting the PI and Adrian Arias - HERE
Single Cell and Synthetic Genomics of Blood Formation
PROJECT DESCRIPTION
Synthetic Enhancers / Functional Genetic Screens / Gene Regulation / Hematopoiesis
The hematopoietic system supplies our body with a trillion new blood cells each day. Evidently, the ability to create this massive number of healthy cells with unique functions requires a fine interplay of gene expression programs. In our lab we try to understand how lineage differentiation and activation of blood stem cells are regulated and encoded in the genome. Specifically, we investigate the role of gene regulatory elements (GREs) such as enhancers using high-throughput functional genetic screens at single-cell, as well as bulk level. These screens allow us to profile the activity of thousands of endogenous and synthetically designed GREs in different cell types across the hematopoietic landscape.
In this project, we propose to investigate how the depletion of key cofactors of transcription affects GRE activity. For this, we performed a high-throughput genetic screen to measure the effect of the knockdown of over 100 cofactors on 100 fully synthetic enhancers. The resulting data is now ideally suited to study the interactions between co-factors and transcription factors that regulate differentiation programs in hematopoietic cells.
WHO ARE WE LOOKING FOR?
This is a dry-lab project, although our lab can offer you insights into the wet lab side of this project, as well. The student should be interested in understanding gene regulation, genetic methods (CRISPR, DNA-/RNA-Seq), the hematopoietic system and statistics/data analysis methods. Students from all backgrounds in biological or computer sciences are welcome, although previous experience in programming in R/Python is preferable and having worked with genomic data is a plus but not strictly required. Most importantly, you are a motivated and proactive team player who is keen to learn more about science.
If you are interested please apply by contacting the PI and Julia Ruehle - HERE
Regulatory genomics and diabetes
FERRER Lab - AWARDED
PROJECT DESCRIPTION
Bioinformatic
s / Biostatistics / Single-Cell / Diabetes mellitus / Perturbations
Type 2 diabetes, or T2D, is a major public health problem worldwide. Over 61 million Europeans live with T2D, that induce more than a million premature death per year. It is characterized by a resistance of cells to insulin, coupled with an inability of the β-cells of the pancreatic islets to produce or release sufficient insulin, inducing a high level of glucose in the blood. This dysfunction is due to both genetic and environmental factors. Genetic susceptibility factors, in particular, are largely enhancer variants that influence gene regulation in pancreatic islets. Furthermore, the major genes that are mutated in more severe monogenic forms of diabetes frequently encode transcription factors that are important for β-cells. Therefore, altered β-cell transcriptional programs play a crucial role in diabetes.
Currently, our reference maps to study the transcriptional behavior of β-cells are limited to a single average state. Knowledge of pancreatic islet cells facing all possible perturbations, both genetic and chemical, could give new insights into the transcriptional networks of β-cells, and how they are altered in diabetes mellitus. A perturbation atlas of human pancreatic islet transcriptional states could provide key knowledge to interpret transcriptional changes observed in single cells from T2D patients. It will allow the functional annotation of perturbed programs that respond genes to distinct signals, and provide a valuable resource to discover drug candidates that revert abnormal transcriptional states.
The HuPIPA project (Human Pancreatic Islets Perturbation Atlas) aims to establish the first perturbations atlas, exposing primary human pancreatic islets to multiple chemical and genetic perturbations and examine their transcriptional and chromatin landscapes at single cell resolution. This should provide a major reference for the field.
WHO ARE WE LOOKING FOR?
We are seeking a master’s student currently enrolled in Bioinformatics, Biostatistics, Machine Learning, or a related field, with strong programming skills in R and/or Python and proficiency in UNIX environments. Experience or interest in genomics and next-generation sequencing technologies is highly valued. The candidate should have excellent problem-solving skills, the ability to work independently, and collaborate effectively within a team. Proficiency in English is required.
If you are interested please apply by contacting the PI and Fanny Mollandin - HERE
Reprogramming and Regeneration
COSMA Lab - AWARDED
PROJECT DESCRIPTION: Combining Super-Resolution microscopy and Artificial Intelligence to detect preleukemia
AML / Super-Resolution Microscopy / Deep Learning / AI / Chromatin Signature
Early detection of cancerous lesions holds a promising potential in terms of management and prevention of the disease. This would increase the possibility of reducing cancer mortality, as proven by the recent advent of screenings for breast, lungs and prostate cancer. Early detection of premalignant neoplastic stem cells would therefore have a great diagnostic and prognostic impact on acute myeloid leukemia (AML), which is now only detected when the cancer is at the latest stages of its development and patients present symptoms.
Initial work in the laboratory led to the design of an Artificial Intelligent (AI) approach to accurately determine the pluripotency gradient of human induced pluripotent stem cells (iPSCs) based on the nuclear distribution and density of RNA Polymerase II and of the DNA fiber.
The aim of the study is to validate this model on different stages of AML and employ our knowledge on nuclear proteins arrangement to identify a chromatin signature able to recognize premalignant cells. This will be done in combination with Super-Resolution (SR) microscopy, a powerful imaging tool which enables the visualization of almost any nuclear component with nanometric resolution, fostering the study of the relation between nuclear organization and cell identity.
WHO ARE WE LOOKING FOR?
We look for a student that is eager to learn both wet lab techniques and bioinformatics. The student should be enthusiastic about the project and the research of our lab. Overall he/she should be passionate about research and the scientific world. The student should have solid theoretical knowledge of cellular and molecular biology. Prior laboratory experience on basic molecular and biochemical techniques is a plus but not a requirement.
If you are interested please apply by contacting the PI and Carlotta Viana - HERE
The epigenetic face of cancer metabolism
SDELCI Lab - AWARDED
PROJECT DESCRIPTION:
Functional Genomics / Lung Adenocarcinoma / TP53 / KRAS / Cancer Metabolism / Metabolic Vulnerability / Molecular & Cellular Biology / Gene Expression / Drug Combination / Targeted Therapies
The co-occurrence of mutations in TP53 and KRAS causes the emergence of lung tumors characterized by a particularly aggressive phenotype. Synthetic lethality in this type of tumor has not been explored and its identification could lead to targeted therapies that would improve the quality of life and life expectancy of patients. This project aims to validate a functional genetic screen performed in lung adenocarcinoma cells with concomitant mutations (KRASG12D/TP53null) to identify metabolic vulnerabilities. The rationale for focusing on metabolic synthetic lethality stems from the fact that inhibitors have been identified for the majority of metabolic enzymes and this could lead to the straightforward proposition of small molecules to treat lung adenocarcinoma patients carrying this genetic asset. Our screening identified vulnerabilities in several metabolic pathways. These findings were corroborated by data analysis from public databases. To further validate these susceptibilities, we will employ gene engineering techniques such as short hairpin RNA (shRNA) to modulate gene expression and pharmacological inhibition to reduce enzyme activity, using both 2D and 3D cell culture models. Once these experiments are performed, the PhD student supervising the MS student will perform in vivo validation in the appropriate orthotopic lung adenocarcinoma mouse models and patient derived xenograft. In addition, we will investigate the underlying mechanisms using multi-omics approaches to assess changes in gene expression and epigenetics, which may lead to the identification of molecular pathways to target for novel therapeutic approaches. Finally, we will explore combinatorial inhibition strategies targeting validated susceptibilities to further increase the likelihood of identifying a successful targeted therapy for KRAS/TP53 mutant lung adenocarcinoma.
WHO ARE WE LOOKING FOR?
The student should have a genuine passion for scientific research, with a strong curiosity to explore new ideas and tackle challenging questions. A positive attitude and willingness to contribute to ongoing research is essential. In addition, a willingness to learn and master new techniques is crucial, as the project may require the use of different experimental methods.
If you are interested please apply by contacting the PI and Julia Urgel - HERE
Genetic Systems
LEHNER Lab - AWARDED
PROJECT DESCRIPTION:
Intrinsically Disordered / Deep Mutational Scanning / Bioinformatics / Molecular Biology / Yeast / Next Generation Sequencing / Proteins / 
Functional Genomics
In recent years there have been large advances in our understanding of how protein sequences encode structure and function, especially in proteins that have well-defined structures. However, our understanding of how sequence maps to function in intrinsically disordered regions (IDRs) that do not have stable structures is comparatively lacking, especially in terms of large-scale perturbation and interpretation of variants. One way of addressing this gap is to use deep mutational scanning to assay thousands of protein variants in parallel, directly linking protein sequence to biophysical function. The aim of this project is thus to adapt existing assays to understand the biophysical and functional encoding of IDRs through the deep mutational scanning framework. This will involve generating large-scale libraries of protein variants and assaying their functions in parallel via assays that select for e.g. protein binding or solubility. The generated data will be used for modeling how protein sequences and their features are related to these biophysical functions, advancing our knowledge of how these sequences encode function in the disordered proteome at scale.
WHO ARE WE LOOKING FOR?
Basic skills/knowledge of molecular biology and bioinformatics with excitement to learn more.
If you are interested please apply by contacting the PI and Taraneh Zarin - HERE
Genetic Systems
PROJECT DESCRIPTION:
Deep Mutational Scanning / Protein Kinases / Conformational Changes / Allostery / Protein Dynamics
Protein kinases are enzymes that regulate various cellular processes by phosphorylation - the transfer of phosphate groups from ATP to specific target proteins. This modification alters the activity, localization, or function of the proteins, playing a crucial role in signal transduction, cell growth, and metabolism. To achieve dynamic regulation, protein kinases function as molecular switches, transitioning between active and inactive forms in response to cellular signals.
In this project, we aim to improve our understanding of the mechanisms of protein kinase activation through deep mutagenesis of the human protein kinase Src. Src, the first known oncogene, is a multi-domain protein, formed by a kinase domain responsible for the catalytic activity, and additional regulatory domains that control the activity of the kinase domain. In the inactive ‘closed’ state, the regulatory domains form intramolecular interactions with the kinase domain, leading to allosteric inhibition, that is, at a distance from the active site. The loss of these interactions during kinase activation, leading to an ‘open’ extended conformation, is thought to contribute to the transition of the kinase domain to an active state. However, the extent to which activation is coupled to these interactions is unknown.
We have recently measured the effects of all possible kinase domain mutations on the cellular abundance and activity of Src, and used thermodynamic models to reveal the first complete map of allosteric communication in a protein kinase domain (Beltran et al., 2024). These maps are, however, agnostic to the conformational state of the kinase. In this project, we will measure how all possible mutations in the kinase domain affect the conformational state of Src. By integrating these measurements with our previous activity and abundance measurements, we will be able to test to what extent Src activation is dependent on the overall conformation of the kinase, and whether it is possible to decouple activation from conformation. This work will advance our understanding of the fundamental mechanisms that regulate protein kinase function.
Beltran A., Faure A., Lehner B. (2024). The allosteric landscape of the Src kinase. bioRxiv. https://doi.org/10.1101/2024.04.26.591297
WHO ARE WE LOOKING FOR?
A background in molecular biology, including cloning and PCR is essential. Previous experience in genomics, high-throughput sequencing, and high-throughput screening technologies would be desirable. Some experience in sequencing data analysis, R and python programming would also be desirable but not essential.
If you are interested please apply by contacting the PI and Antoni Beltran- HERE
Single Cell Epigenomics and Cancer Development
PROJECT DESCRIPTION:
Cancer / Gene Editing / Gene Regulation / CRISPR-Cas9
Non-Hodgkin lymphomas, such as mantle cell lymphoma (MCL), frequently arise upon the t(11;14) chromosomal translocation in B cells, driving CCND1 upregulation via the immunoglobulin heavy chain (IGH) enhancer. Much research has focussed on the short-range in cis effects of the IGH enhancer at the chromosomal breakpoint, however, whilst gene expression is often altered across entire translocated chromosomes, understanding of the extended translocation-based effects and their functional consequences are limited. Furthermore, whilst the IGH-mediated upregulation of CCND1 on the translocated derivative 14 chromosome have been extensively studied, there is extremely limited understanding of broader gene-regulatory effects on this derivative as well as the effects of t(11;14) on the other translocated derivative chromosome 11 of which no longer contains CCND1.
Preliminary findings from the host lab combining allele-specific chromatin conformation capture, in silico modelling and imaging, show that this translocation leads to an inwards shift in nuclear positioning of derivative 11, placing it within a more permissive environment for gene expression activation. Additionally, in MCL patient samples, chromosome 11 shows an increased number of upregulated genes, particularly downstream of the translocation breakpoint.
Based on the abovementioned results, we hypothesise that t(11;14) favours upregulation of a subset of genes - beyond CCND1 – that drive lymphoma formation This project aims to characterise the functional impact of t(11;14), by investigating the upregulated genes present on chromosome 11 in MCL, and identify key driver genes implicated in the initial stages of lymphomagenesis.
Based on preliminary RNA-seq data of MCL patient samples, the student will perform a pooled CRISPR/Cas9 knockout (KO) screen in MCL cell lines targeting approximately 120 significantly upregulated genes on chromosome 11. Cells will then be cultured for phenotypic analyses, including proliferation (via CellTiter Glo) and invasion (via invasion assays), and genomic DNA isolated on days 0, 7 and 14 for analysis via next generation sequencing. This will allow the identification of gRNAs that infer proliferative or invasive disadvantage, and thus genes that are involved in these processes. Approximately 5-10 of the top gene candidates will then be functionally validated for tumourigenic impact via single gene CRISPR/Cas9 KO experiments and further phenotypic assays. Overall, this will allow the identification of new driver genes present on the largely overlooked chromosome 11 in MCL, enabling the further understanding of novel molecular mechanisms underpinning lymphomagenesis.
WHO ARE WE LOOKING FOR?
In order to pursue this project, the student requires solid hands-on experience in cellular and molecular biology techniques, including mammalian cell culture, lentiviral transfections, CRISPR and PCR/qPCR. Experience in functional assays of proliferation and invasion, as well as western blotting and next generation sequencing, are also desirable but not essential. Furthermore, a strong understanding of cancer biology and molecular biology is needed.
If you are interested please apply by contacting the PI and Chloe Gulliver- HERE
Dynamics of Living Systems
PROJECT DESCRIPTION - Designing a protein degradation technology orthogonal to the AID system
Synthetic Biology / Gene Regulation / Spatiotemporal Control / Protein Degradation / CRISPR
The physiological mechanisms governing health and disease exhibit complex interactions between multiple genes and gene products. To study the dynamics of living systems, researchers need experimental methods capable of producing calibrated, quantitative perturbations in vivo — perturbations that cannot be obtained using classical genetics, RNAi interference, or small molecule drugs. Recently, an auxin-inducible degron (AID) system has been developed to allow targeted degradation of proteins using small-molecule activators, providing spatiotemporal control of protein abundance. However, a major limitation of this technology is that it only allows the targeted protein degradation of one gene product at a time. To overcome this limitation, we plan to design an orthogonal protein degradation system and to test its functionality in the model organism Caenorhabditis elegans. In this project, we will follow up on our work to engineer new and better versions of the AID system (Vicencio et al., 2024, bioRxiv) by using CRISPR genome engineering to build new degron systems for advanced interventions in physiology and aging.
WHO ARE WE LOOKING FOR?
We are seeking a motivated student pursuing a degree in Biology, Biochemistry, Genetics, Molecular Biology, or Biomedicine with foundational knowledge of bioinformatics tools for sequence annotation. The ideal candidate will have hands-on experience in wet lab environments, proficiency in basic molecular biology techniques, a keen interest in CRISPR-Cas systems and transgenesis, as well as strong data visualization and analysis skills.
If you are interested please apply by contacting the PI and Jeremy Vicencio - HERE
Single cell genomics and evolution
PROJECT DESCRIPTION - Chromatin dynamics during Nematostella development
Development / Genome Regulation / Computational Biology / Omics Analysis / Functional Genomics
At Sebe-Pedros lab we have developed the experimental and computational tools to assess the epigenomic landscape of the cnidarian Nematostella vectensis adult cell types: iChIP of selected histone post-translational modifications; micro-C chromatin contact maps; and the Assay for Transposase Accessible Chromatin (ATAC) sequencing. Now, we want to unravel how those cell type landscapes unfold during development and identify key features of developmental gene regulation. To this end, we have used iChip, ATACseq and micro-C to profile the chromatin landscapes of different embryonic stages that capture major developmental transitions in Nematostella (i.e. Maternal-Zygotic Transition, Germ layer specification, and tissue differentiation). The main goal of the master student’s project is to contribute to the generation of these datasets and to work on the computational integration of this epigenomics data to define the developmental gene regulatory landscapes in this pre-bilaterian model species. Finally, the master student will participate in the in vivo validation of some of his/her predictions using shRNA against key TFs and scRNAseq phenotyping.
WHO ARE WE LOOKING FOR?
We are looking for a candidate with a hybrid profile, combining both dry and wet lab expertise. The ideal candidate is pursuing a Master’s in Genomics or Bioinformatics, with a Bachelor's degree in Biology, Biomedicine, or a related field. They should have basic knowledge of epigenetics and development, programming skills in R or other scripting languages (Python/Perl), and experience working in Linux environments. Additionally, the candidate should possess basic molecular biology skills, such as PCR and cloning, and demonstrate a collaborative and friendly attitude. Optional but desirable skills include experience in omics data analysis, working with embryos, and utilizing HPC clusters.
If you are interested please apply by contacting the PI and Marta Iglesias - HERE
ROSA MARTINEZ CORRAL Lab
PROJECT DESCRIPTION
Transcription Regulation / Chromatin Dynamics / Equilibrium Models / Non-Equilibrium Models
In the fascinating early stages of Drosophila development, embryos undergo a series of rapid nuclear divisions—known as nuclear cycles (NC)—without cytokinesis. After nuclear cycle 10 (NC10), the interphases lengthen, making transcription detectable. However, during the following transcriptionally active cycles, the interval between nuclear divisions remains short (approximately 10 minutes), highlighting an important relationship between transcription and the dynamics of chromatin condensation. The details of how to quantitatively model and understand this coupling remain largely unexplored.
This project aims to address this challenge by developing both equilibrium and non-equilibrium models of transcription regulation linked to chromatin dynamics. The student will rigorously test various biophysical assumptions using advanced techniques from dynamical systems modelling, linear frameworks, and statistical mechanics. The theoretical insights gained will be compared with recent experimental data from the MS2-MCP reporter system. Ultimately, this work seeks to foster collaboration with experimentalists, paving the way for new experiments that can enhance our understanding of transcriptional regulation in Drosophila.
WHO ARE WE LOOKING FOR?
The student must have previous experience with simple mathematical modelling of biological systems, e.g. using systems of ordinary differential equations. The ideal student should have basic knowledge of molecular biology, in particular, transcription regulation, and some physics knowledge, particularly the basics of thermodynamics. Also, the student must have some basic programming experience in Python, R, or Julia. The student should be motivated to learn about new physics, biology, and mathematical methods and become an independent and critical thinker, not only executing assigned tasks.
If you are interested please apply by contacting the PI and Giorgio Ravanelli - HERE
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Fellowships conditions
- 600€/month – up to 5 months
- Return ticket (800€/non European flight – 300€/European flight)
- The fellowship can only be given to new recruits, not students already at the CRG
- The fellowship needs to be given within the academic year 2024/2025
Please contact the lab directly and attach the following documents:
- Motivation letter
- CV
- Reference letter
- University transcripts
Contact
For any further questions, please contact
CRG Training & Academic Office
Centre de Regulació Genòmica
Dr. Aiguader, 88
PRBB Building
08003 Barcelona
training@crg.eu