PhD position in Machine-learning-enabled Substrate Specificity Analysis of Carbohydrate-acting Enzymes from the Gut Microbiome, Wageningen University, Netherlands, Europe

Last Date: 15 April 2024.

Your job

Would you like to participate in an exciting interdisciplinary applied science project involving both academic and industry partners to study how the microbiome is able to help humans digest diverse fibers? Do you enjoy collaboration and teamwork while being at the cutting edge of scientific progress? If yes , then this may be the perfect position for you!

The Host-Microbe Interactomics Group together with Bioinformatics Group at Wageningen University are looking for a PhD candidate with expertise in protein structure bioinformatics and machine learning, who is also not afraid to participate in wet-lab experiments to generate the best possible training datasets.

The human gut microbiome plays a crucial role in our health, and consuming dietary fiber has been shown to significantly impact its composition and metabolic function. However, many people in industrialized countries lack sufficient fiber intake, which can lead to a decline in gut microbial diversity and reduced production of health-promoting compounds.

Metagenomic sequencing of the gut microbiome has generated a catalogue of carbohydrate-active enzymes (CAZymes) that can be found in the human gut microbiome, which are responsible for degrading dietary fibers and generating beneficial metabolites. To capitalize on this knowledgebase, the ambitious FIBERME project aims to use Artificial Intelligence (AI) to predict the human microbiome’s response to dietary fibers.

Within this public-private partnership, a PhD position is available within the Host-Microbe Interactomics and Bioinformatics chair groups at WUR.

In this project, you will use microbiome data mining approaches in combination with results obtained in high-throughput functional screens to chart the functional diversity of CAZymes in the human gut. Based on these data, you will train state-of-the-art machine learning models based on both sequence and structural features to predict the substrate specificities and catalytic activities of these enzymes. Iterative feedback cycles between computational models and wet-lab experiments that will be performed within the FIBERME project will lead to increasingly accurate predictions of enzyme function that can be validated within the FIBERME project via microbiome analyses obtained during fiber consumption intervention trials in healthy volunteers.

Your qualities

We are looking for an enthusiastic team player with all or a subset of the following skills:

  • a solid academic record (MSc) in bioinformatics, biochemistry, microbiology or a related discipline
  • experience in computational omics analysis and proficiency in programming (in, e.g., Python)
  • at least basic to intermediate statistical and mathematical skills
  • demonstrable experience in working with protein structure data and/or machine learning
  • affinity with microbiology and metabolism
  • team player attitude, enjoying multidisciplinary science
  • a very good level of oral and written English. You are required to show us a certification of English skills. For this position your command of the English language is expected to be at C1 level. Sometimes it is necessary to submit an internationally recognised Certificate of Proficiency in the English Language. More information can be found here.
  • you meet all the entry requirements of the WUR PhD programme.

We offer you

Wageningen University & Research offers excellent terms of employment. A few highlights from our Collective Labour Agreement include:

  • Partially paid parental leave;
  • working hours that can be discussed and arranged so that they allow for the best possible work-life balance;
  • the option to accrue additional compensation / holiday hours by working more, up to 40 hours per week;
  • there is a strong focus on vitality and you can make use of the sports facilities available on campus for a small fee;
  • a fixed December bonus of 8.3%;
  • excellent pension scheme.

In addition to these first-rate employee benefits, you will receive a fully funded PhD position and you will be offered a course program tailored to your needs and the research team.
The gross salary for the first year is € 2.770 – per month rising to € 3.539,-  in the fourth year in according to the Collective Labour Agreements for Dutch Universities (CAO-NU) (scale P). This is based on a full-time working week of 38 hours. We offer a temporary contract for 18 months which will be extended for the duration of the project if you perform well.

There are plenty of options for personal initiative in a learning environment, and we provide excellent training opportunities. We are offering a unique position in an international environment with a pleasant and open working atmosphere.

You are going to work at the greenest and most innovative campus in Holland, and at a university that has been chosen as the “Best University” in the Netherlands for the 19th consecutive time.

Coming from abroad
Wageningen University & Research is the university and research centre for life sciences. The themes we deal with are relevant to everyone around the world and Wageningen, therefore, has a large international community and a lot to offer to international employees.
Our team of advisors on Dutch immigration procedures will help you with the visa application procedures for yourself and, if applicable, for your family.
Feeling welcome also has everything to do with being well informed. Wageningen University & Research’s International Community page contains practical information about what we can do to support international employees and students coming to Wageningen. Furthermore, we can assist you with any additional advice and information about for example helping your partner to find a job, housing, or schooling. Finally, certain categories of international staff may be eligible for a tax exemption on a part of their salary during the first five years in the Netherlands.

Apply

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