Do you have experience in computational biology, machine learning, and artificial intelligence (AI), and are you interested in resolving big data-driven fundamental research questions in the green life sciences? Then come and join our new interdepartmental AI Technology for Life group and the Plant-Microbe Interactions group as an Assistant Professor.
The green life sciences research field is increasingly becoming data-driven. Technological developments have resulted in experimental methods producing vast amounts of data (e.g. next-generation sequencing or other omics techniques, high-throughput phenotyping). In the Plant-Microbe Interactions field this includes big data sets from high-density time series RNA-seq, single cell sequencing, microbiomics and metagenomics studies that describe interactions between host plants and their microbiota.
Hence, the analysis, interpretation, and integration of different types of big data is becoming more and more complex. To address current and future questions in green life sciences research, it is crucial to invest in novel and powerful machine learning approaches, such as explainable AI, symbolic learning, graph neural networks, autoencoders and/or attention based models, that can help to explain the complex patterns hidden in this data. Such approaches will enable us to address novel, next-level biological research questions.
Translation of the developed AI technology and resulting discoveries to the application will contribute to solving real-world problems. Computational biology and bioinformatics are already well developed within the Faculty of Science, but would highly benefit from explainable machine learning methodology. Therefore, a synergistic collaboration between the Departments of Biology and Information and Computing Sciences is established, resulting in the AI Technology for Life cluster within the Faculty of Science.
The AI Technology for Life group focusses on explainable AI, with applications in the Life Sciences. You will be part of the Plant-Microbe Interactions (PMI) team of the department of Biology and of the new interdepartmental AI Technology for Life group, which is affiliated both with the Department of Information and Computing Sciences and the Department of Biology. The PMI team is focused on unraveling the dynamics and complexity of root-microbiome interactions and of gene regulatory networks that steer the plant immune system. You will strengthen these two groups and are encouraged to join forces with other life scientists and computer scientists at Utrecht Science Park to build your independent research group.
As an Assistant Professor you will actively engage in research, teaching, and supervision. You have proven research and teaching skills, and can develop an independent research line at the interface of Plant-Microbe Interactions and AI Technology for Life. At the same time, you are able to connect to, complement, or extend other research themes in the department of Biology, the department of Information and Computing Sciences, and beyond.
To further build our team, we consider it important that you can think critically and creatively and have strongly developed social skills. You have the capacity and interest to develop leadership skills for a future staff position in the Plant-Microbe Interactions group and the AI Technology for Life group.
If you are excited to play a connecting role at the interface of AI and the green life sciences we invite you to apply.
We are looking for a dedicated, creative, and collaborative scientist who is enthusiastic about working with us to further shape the new cluster. You have a track record in developing machine learning technology and its application in modern life sciences research, which is evident from your publications with impact in international conferences and journals. Your experience allows you to be at ease with diverse types of experimental data: molecular (e.g. DNA/RNA/protein sequences), organismal (e.g. phenotypes of whole plants), and/or other experimental data types. We would also like you to meet the following criteria:
- a PhD in Computer Science, AI, Data Science or a relevant life sciences discipline with a focus on machine learning;
- you have research experience in machine learning and handling large (gen)omics data sets;
- ideally you have research experience or interest in the area of microbial and/or plant biology;
- you have experience, talent and interest in academic teaching;
- proficiency in English (speaking and writing) and willingness to learn Dutch;
- experience with publishing impactful science;
- a network in your science field and experience with outreach, demonstrated experience and success in acquiring external funding.
- an appointment as Assistant Professor, starting with a fixed term contract. Following a positive evaluation after 18 months, this will be converted in a permanent contract;
- we offer you a development track during the first 3 years of your employment. We will set goals together and support you to reach these and grow both professionally and personally;
- a full-time gross salary – depending on previous qualifications and experience – ranging between €3,974 and €5,439 per month (scale 11 at the level of Assistant Professor (universitair docent; UD) according to the Collective Labour Agreement Dutch Universities (CAO));
- benefits including 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.
- you will be able to co-supervise a funded PhD student, together with the AI technology for Life and Plant-Microbe Interactions groups.
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 and sports. 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.
Do you have a question about the application procedure? Please send an email to email@example.com
Everyone deserves to feel at home at our university. We welcome employees with a wide variety of backgrounds and perspectives.
If you have the expertise and the experience to excel in this role, please respond via the “Apply” button, enclosing:
- your letter of motivation, in which you outline how you fulfil the requirements for this position.
- your curriculum vitae, including a publication list, and your top 3 publications – with motivation;
- a research vision (2-3 pages and please include how you envision the embedding of your research in the Plant-Microbe Interactions and AI technology for Life groups, and/or in the green life sciences at large);
- a teaching vision (1 page);
- the names and email addresses of three references;
- a copy of your PhD certificate.
The application deadline is 23 January 2023.