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. More information about ongoing research, publications and media can be found here.

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 (e.g. Robert Mans, Biotechnology) as well as internationally (the Baym lab at Harvard Medical School). 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 TUDelft and nationally, in which you may also assist.

We value different perspectives and we strongly believe that diversity drives innovation. We offer an open and safe working environment for employees and students regardless of their nationality, cultural background, gender or sexual orientation. Anyone who meets the application criteria and whose curiosity was triggered by the description above is strongly encouraged to apply.

To be considered for the position you must:

• have a master’s degree (or equivalent) in Computer Science, Bioinformatics, Mathematics or a closely related field.
• have strong computational skills in algorithm design and data analysis.
• have a strong interest in bioinformatics. Prior experience in this field is beneficial but not strictly necessary.
• 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.     

Fixed-term contract: 4 years.

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2434 per month in the first year to € 3111 in the fourth year. 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

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. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.