Three PhD positions in AI for the Life Sciences (0.8 - 1.0 FTE)

1. PhD in AI Technology for plant-microbiome interactions.
   In this project you will develop methodology to understand the interactions between plant root systems and their associated microbiome. The project aims to investigate the fundamental principles underlying complex microbial community assembly on plant roots and therefore provide knowledge that can be used to improve growth and stress resilience of our crops. Your work will involve analysing complex synthetic communities with diverse microorganisms sourced from different plants. These communities exhibit various functional properties, influencing plant phenotypic outcomes. You will evaluate the contribution of specific functional properties, such as catabolic pathways, and community network properties like microbial cross-feeding and competition to the establishment of the root-associated microbiome and ultimately plant productivity. The objective is to develop methodology to understand and predict community assembly outcomes and plant productivity in both simulated and real-world environments. You will work closely together with experimental plant groups at the Biology department.  Your predictions and findings will inspire subsequent experiments, creating a feedback loop that enriches the project's outcomes.
2. PhD in Explainable AI for Multi-Modal Life Science Data.
   In this project, you will develop explainable AI methodologies for data in the Life Sciences. This project will focus on building generalizable and inherently interpretable models, generating explanations alongside predictions. Deep representation learning strategies will be developed to find the best and most interpretable semantic space combining imaging and tabular/multi-omics information. The methodology will be applied to medical data (images, and clinical information) and/or plants.
3. PhD in explainable AI in a multi-task setting.
   You will develop AI methodology to derive explanations for multi-task prediction models. In other words, there will be multi-modal learning objectives. You will further develop a multi-task deep learning model that can handle this type of data, and develop methodology that can explain predictions through related tasks. The applications are in the biomedical domain in neurodegenerative disease and/or in an oncology setting, using protein sequence, function and structure and/or multi-omics data.

You will become part of the vibrant interdisciplinary research group “AI Technology for Life”, a new interdepartmental research group between the Department of Information and Computing Sciences and the Department of Biology. The group is created as a result of the great importance attached by the Faculty of Science to stimulate research and teaching between departments. Together with the members of the group you work at the interface between the Life Sciences and AI.

• A (nearly) completed MSc degree in a relevant area such as Artificial Intelligence or Bioinformatics with a strong AI component;
• Demonstrable experience with development of machine learning methods;
• An interest in working with life science data, for example omics data or medical images;
• As you will have to collaborate with researchers in the life sciences, it is essential that you have strong oral and written communication skills in English.

We offer a position for 4 years, which includes the following:

• a full-time gross salary that starts at €2,770 and increases to €3,539 per month (scale P of the Collective Labour Agreement Dutch Universities (cao));
• 8% holiday bonus and 8.3% end-of-year bonus;
• a pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.

If you enjoy teaching and would like to develop further in this, we offer you the possibility of a 5-year contract. You will then spend 30% of your time on teaching activities.

In addition to the employment conditions from the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. These include agreements on professional development, leave arrangements, sports and cultural schemes and you get discounts on software and other IT products. We also give you the opportunity to expand your terms of employment through the Employment Conditions Selection Model. This is how we encourage you to grow.

For more information, please visit working at Utrecht University.

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Shaping science, sharing tomorrow.

At the Faculty of Science, there are 6 departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences, and Physics. Each of these is made up of distinct institutes that work together to focus on answering some of humanity’s most pressing problems. More fundamental still are the individual research groups – the building blocks of our ambitious scientific projects. Find out more about us on YouTube.

You will be embedded in the interdepartmental research group AI Technology for Life, and affiliated with both the Department of Biology and the Department of Information and Computing Sciences.

Everyone deserves to feel at home at our university. We welcome employees with a wide variety of backgrounds and perspectives. 

If you are enthusiastic about this position, just apply via the "Apply" button! Please enclose:

• your letter of motivation in which you;
  • clearly indicate which position (1, 2 or 3) you are interested in;
  • motivate why you are interested in the position and how your previous experience makes you suitable for the position.
• your curriculum vitae;
• the names, telephone numbers, and email addresses of at least two references;
• a copy of your MSc thesis (if available).

If this specific opportunity isn’t for you, but you know someone else who may be interested, please forward this vacancy to them.

*Note to recruitment agencies: Please refrain from contacting us regarding this job posting.

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