PhD Position Algorithms for Microbial Genomics

Do you want to contribute to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics!

Job description

Bacterial and viral infections pose one of the biggest threats to human health. Genomic mutations (i.e. changes to the genome sequence) can affect characteristics of the pathogen, such as virulence, drug response and vaccine escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately.

Genomes are studied through genome sequencing, but these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able to track how the prevalences of different strains in a mixed sample change over time.

Your role:

You will develop and implement algorithms to find, quantify and track mutations in evolving populations of viruses, bacteria and/or yeasts. Some challenges that you will be facing are:

• How to distinguish genomic mutations from sequencing errors using the latest sequencing technologies?
• How to distinguish mutations in a given gene from mutations in homologous genes?
• How to deal with large-scale structural variation?
• How to link mutations together into genomes across distances longer than the read length?

You will address these challenges by formulating appropriate graph optimization problems (e.g. minimal edge covering, minimal path covering, shortest paths, clustering) and solve these problems using techniques such as linear/integer programming or by designing suitable heuristics.

The algorithms that you develop can play an important role in pathogen surveillance, infection treatment design, and/or understanding evolution. Depending on your expertise and interests, your projects can be more applied (in collaboration with experimental groups) or more theoretical.

You will be part of the Delft Bioinformatics Lab in the Intelligent Systems department at TU Delft. In this project we also work together with experimental groups at TU Delft and beyond. The Delft Bioinformatics Lab has strong algorithmic and machine learning expertise, with a profound interest in new biomolecular technologies. We teach bioinformatics courses across several programs within TU Delft and nationally, in which you will also assist.

Job requirements

To be considered for the position you must:

• Have a master’s degree (or equivalent) in Computer Science.
• Have strong computational skills in algorithm design and data analysis.
• Have experience with courses and projects in Bioinformatics.
• Have experience with programming and/or software engineering. Strong programming skills are a definite plus.
• Have good communication skills in English (both verbal and written).
• Be eager to push yourself to learn new skills, exchange knowledge and collaborate where possible.
• Be willing to teach and guide students.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Dr. Jasmijn Baaijens, via j.a.baaijens@tudelft.nl.