PostDoc – Machine learning towards studying meiotic recombination
|Published||November 28, 2022|
We are looking for
Are you a talented, motivated researcher who is interested in the application of advanced computational techniques to study fundamental genetic processes in plants and fungi? Do you want to develop and apply machine learning approaches in order to study a variety of genomics datasets? Are you able to collaborate with different researchers, such as bioinformaticians, geneticists and plant breeders in order to unravel underlying determinants of meiotic recombination?
You will develop generally applicable methodologies that can be applied to various datasets from different species available at GBU, including plants and fungi. You will analyze the crossover landscapes in these datasets, building on a currently available machine learning model. You will extend the model to incorporate the effect of structural and allelic variation, and you will use the model to analyze the effect of meiotic recombination on genetic variation in genes of interest, in particular disease resistance genes.
This is what you are going to do:
• carry out computational method development;
• closely work together with researchers from GBU that provide datasets;
• analyze these datasets and integrate analyses from different species.
The Postdoc project is funded by GBU in order to foster collaboration between the various participating groups. An important aspect of this postdoc position will be to organize and stimulate dissemination activities and interactions between the different partners involved. Your main supervisor will be Dr. Aalt-Jan van Dijk in the Bioinformatics group. A broad range of relevant expertise is available in this group, in particular on the development and application of machine learning to biological processes. Other collaborators from the different groups in GBU include Ben Auxier, Yuling Bai, Guusje Bonnema, Klaas Bouwmeester, Paul Fransz, Martina Juranic, Arend van Peer, Sander Peters, Henk Schouten and Eveline Snelders.
Meiosis is an essential process to ensure that the correct number of chromosomes is retained during sexual reproduction. It involves the formation of recombination events or crossovers between homologous chromosomes. These crossovers do not occur randomly over the chromosome. A better understanding of what drives their preferential localization is of fundamental scientific interest, and will lead to great practical benefits for plant breeding. We are looking for a two-year postdoc to apply machine learning to study various available datasets on plant and fungal meiotic recombination. The position is part of a collaboration between four research groups (Bioinformatics, Biosystematics, Genetics, and Plant Breeding) in the Genome Biology Unit (GBU) of Wageningen University & Research.
Your profile demonstrates:
- a PhD degree in a relevant field, e.g. bioinformatics, computational biology, biosystematics, plant sciences, plant breeding or genetics;
- hands-on experience and interest in developing technologies towards analyzing genome datasets from various species;
- the motivation to initiate and organize collaborations between the different research groups involved in the project;
- excellent analytical, communication and scientific writing skills.
In addition, given the importance of both computational skills as well as understanding of relevant biology, candidates matching one of the following two points will be selected with priority:
- proven experience with machine learning and interest in applying these technologies to biological processes;
- knowledge of molecular processes such as meiotic recombination and interest in applying machine learning to study such processes.
Wageningen University & Research offers excellent terms of employment. A few highlights from our Collective Labour Agreement include:
- study leave and 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 of course receive a good salary. Depending on your experience, we offer a competitive gross salary of between € 2.960,- and € 4.670,- for a full-time working week of 38 hours, in accordance with the Collective Labour Agreements for Dutch Universities (CAO-NU) (scale 10). Additionally, a contract for 0.8 FTE can be discussed.
Wageningen University & Research encourages internal advancement opportunities and mobility with an internal recruitment policy. 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 17th 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. Applicants from abroad moving to the Netherlands may qualify for a special tax relief, known as the 30% ruling. 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 helping your partner to find a job, housing, schooling, and other issues.
For more information about this position, please contact dr. Aalt-Jan van Dijk, associate professor bioinformatics, by e-mail at firstname.lastname@example.org. For more information about the procedure, please contact email@example.com.
Do you want to apply?
You can apply directly using the apply button on the vacancy page on our website which will allow us to process your personal information with your approval.
This vacancy will be listed up to and including December 12, 2022. We will schedule the first job interviews January 2023.
Wageningen University & Research (WUR) employs a large number of people with very different backgrounds and qualities, who inspire and motivate each other. We want every talent to feel at home in our organisation and be offered the same career opportunities. We therefore especially welcome applications from people who are underrepresented at WUR. For more information please go to our inclusivity page. A good example of how WUR deals with inclusiveness can be read on the page working at WUR with a functional impairment.
The mission of Wageningen University & Research is “To explore the potential of nature to improve the quality of life”. Under the banner Wageningen University & Research, Wageningen University and the specialised research institutes of the Wageningen Research Foundation have joined forces in contributing to finding solutions to important questions in the domain of healthy food and living environment. With its roughly 30 branches, 7,200 employees (6,400 fte) and 13,200 students and over 150.000 participants to WUR’s Life Long Learning, Wageningen University & Research is one of the leading organisations in its domain. The unique Wageningen approach lies in its integrated approach to issues and the collaboration between different disciplines.
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We will recruit for the vacancy ourselves, so no employment agencies please. However, sharing in your network is appreciated.