Internships & Projects

Projects and Internships

Bioinformatics Profile Students are expected to at least “do” a bioinformatics project (18EC) however we recommend to go for a 33EC (6 months) internship. On this page we try to list projects that are available trough our community. Of course you are always welcome to find your own group to do an internship (or project). Keep in mind to always discuss with your masters coordinator (tutor) to see if this bioinformatics internship (or project) also fits the requirements of your master.

 


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Your background

Education:

  • University or HBO study in bioinformatics or medical informatics with a major background in data analysis.
  • Biology or life sciences University or HBO degree with a major background in data analytics
  • Understanding of multi-omics data such as microarray and RNAseq data, flow cytometric frequency, protein abundance, genome-wide SNP frequencies
  • Experience using packages such as R or Python

 

Who you are

  • Self-propelled – take initiative to bring things forward
  • Hands-on mentality
  • Team player
  • Experience with processing and interpretation of biological, biochemical and experimental data
  • Affinity with structured analysis, data and workflow modelling
  • Attention to detail
  • English language skills

 

Student job in bioinformatics

Would you like to get involved at the forefront of applying AI & big data technology in life sciences research and work with the leading pharma, biotech and research institutions worldwide? If you are a biology/bioinformatics student with a passion for data processing and analysis, please read on!

We are looking for students to support our platform team for 6 -12 hours per week. The role is primarily focused at processing and integrating all types of multi-omics data to be used in the Euretos AI platform for biological research projects. We have developed a pipeline for integrating annotated databases, experimental data and ontologies into a knowledge graph. You will be operating this pipeline via a graphical user interface to define and test integration configurations.

Euretos

Euretos, ( www.euretos.com ), provides an AI platform mainly used by pre-clinical researchers for in-silico discovery & validation of targets and biomarkers. World leading pharma, biotech and academic institutions use it to accelerate multi-omics research in all major disease areas.

By integrating over 250 different public databases, the platform provides the largest single environment in which the latest multi-omics data is interlinked to literature, experimental and clinical evidence.
We are based on the Utrecht Science Park, Yalelaan 1, 3584 CL, Utrecht.

Your Responsibilities

  • Track changes in original data sources; process changes in the data integration pipeline, and document those changes.
  • Find new relevant public data sources, model and document the integration and process changes in the data integration pipeline.
  • Preprocessing of data, performing meta-analyses where applicable, and documenting the methods.

 

Apply Now!

Do you think you are the right person for the job? Then apply now and:

  • Send an email to information@euretos.com or
  • Contact Aram Krol on linkedIn: https://www.linkedin.com/in/aramkrol/

Research projects topics

  • [Machine learning] Discovering rare DNA micro-topologies using multi-contact chromatin conformation data with single-allele resolution
  • [Bioinformatics] In-silico Unique-Molecule-Identifier (UMI) to discern single-allele conformations in 3rd generation nanopore sequencing technology
  • [Bioinformatics] Mult-way aware aligner to improve long-read (3rd generation) sequencing mapping quality
  • [Visualization] Peaking into higher-order chromatin contacts: visualizing multi-way DNA interactions in the nucleus
  • [Statistical modeling] Association test to distinguish linear proximity of sites in the genome from their 3D interactions

Several research projects in the group of Wouter de Laat

 

There are trillions of cells in the human body performing variety of functions from digestion to pumping blood. Surprisingly, these functions are orchestrated by a somewhat identical 2 meters of DNA tightly folded in their 10 nanometer wide nucleus. Thanks to research by us and others, we now know that the spatial organization of genomes inside their nucleus can influence its function. ​We develop and apply innovative genomics technologies (e.g. 4C and Hi-C​) to interrogate this structure​ and​ further integrate ​our results with transcriptomics and epigenomics data to extract new insights about this complex mechanism​. We recently​ extended these approaches to simultaneously assess 3D​ DNA interactions that occur between multiple genomic loci in single-alleles of ​the DNA. Diverse projects are available to further optimize ​existing (or develop new​) analytical tools ​to ​advance our understanding​ of this fascinating system​

Download the PDF file with the detailed description of all projects

Master projects overview-2

For more information and to apply please contact:

Bioinformatic re-assembly of highly polymorphic plant resistance gene clusters

 

Plant resistance genes encode for receptors that recognize pathogen molecules and trigger an effective immune response. In plant genomes resistance genes are often clustered and highly polymorphic between lines of the same species. This means that the number and DNA sequences of resistance genes is highly variable making it impossible to easily compare these regions between lines. We are now using targeted locus amplication (TLA) followed by NGS to collect sequence reads of these regions. The challenge now is to assembly these reads into correct gene clusters. For this project you will start with Illumina reads of TLA samples and a reference genome. As simple mapping of reads to the reference will not work you will need to make a hybrid approach between mapping and de novo assembly followed by annotation. A method for this does not exist yet, so needs to be develop in the proposed project. A challenging and interesting project that is closely linked to the lab research of our Plant-Microbe Interactions group