Do you enjoy using computational approaches to study biological problems? Are you interested in developing and applying machine learning methodology to investigate enzymes? We invite enthusiastic and dedicated candidates to join our cutting-edge research team as a PhD student to work on developing novel methodology to predict enzyme specificity.
The position is part of the Marie Skłodowska-Curie Network program “Modelling the Biochemistry of Terpene Synthases” also called ModBioTerp. ModBioTerp aims to advance our understanding of terpene synthases using forefront modelling techniques and biochemical characterization to predict and tailor the structure and functionality of these elusive enzymes.
The focus of this project is on the natural product class of terpenoids, which is the largest and most chemically diverse class of natural products and holds immense potential for biotechnological applications. ModBioTerp will establish enzyme models, that predict and ab-initio tailor the structure and functionality of terpene synthases and unlock the vast potential of terpenoids and lead the way towards sustainable and innovative biotechnological solutions.
You will be part of the
Biosystems Data Analysis (BDA) group of the
Swammerdam Institute for Life Sciences. BDA works on the development of methodology for data mining, machine learning/deep learning, data fusion, and modelling and application of these methods to answer biological questions, in close collaboration with domain experts. We recently developed methodology for protein structure-based machine learning, which serves as a basis for the current project.
What are you going to do? You will work on the following research objectives:
1) Develop machine learning methodology to integrate docking results with protein sequence-and structure-features
to predict enzyme specificity.
2) Incorporate predicted protein dynamics as input for enzyme specificity prediction.
3) In collaboration with other researchers in the project, apply the methodology to design enzyme characterization
experiments and predict functionality of new enzymes.
Tasks and responsibilities: You will
- develop machine learning/deep learning approaches, building on recently available enzyme function prediction methodology;
- make use of available enzyme characterization data and data newly obtained by our collaborators, as input for training
machine learning models;
- collaborate with both experimental researchers as well as with computational researchers (other PhD students working in the
ModBioTerp project);
- be an active member of the research group and take responsibility for shared tasks; discuss your work with the group members and
during ModBioTerp meetings; incorporate feedback and give input to others;
- take a leading role in writing manuscripts;
- complete a PhD thesis within the official appointment duration of four years;
- participate in the Faculty of Science PhD training program;
- assist in teaching and supervise Bachelor and Master theses.
Your profile You are passionate about science and have a particular interest in machine learning/deep learning applications in biology. You enjoy close collaboration with domain experts. You have a creative mind and look forward to work at the cutting-edge of computational technology. Finally, you are a team player and a pleasant colleague who enjoys being part of an interdisciplinary team of computational researchers and enzyme scientists.
Your experience and profile: You have/are
- an MSc in Data Science, Artificial Intelligence, Computational Science, Bioinformatics, Systems Biology or similar;
- interested in using machine learning/deep learning on protein sequence- and structure-data;
- able to communicate with non-experts on computational issues;
- professional command of English.
Our offer We offer a temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is January 1st, 2025. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
Based on a full-time appointment (38 hours per week) the gross monthly salary will range from € 2.872 in the first year to € 3.670 (scale P) in the last year. This does not include 8% holiday allowance and 8,3% year-end allowance. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
- 232 holiday hours per year (based on fulltime);
- multiple courses to follow from our Teaching and Learning Centre;
- a complete educational program for PhD students;
- the possibility to follow courses to learn Dutch;
- help with housing for a studio or small apartment when you’re moving from abroad.
Are you curious to read more about our extensive package of secondary employment benefits, take a look
here.
About us The
University of Amsterdam is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.
The
Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are
fascinated by every aspect of how the world works, be it elementary particles, plant molecules, the birth of the universe or the functioning of the brain.
The
Swammerdam Institute for Life Sciences (SILS) is located at the vibrant Amsterdam Science Park. SILS is one of eight institutes of the University of Amsterdam's Faculty of Science (FNWI). With around 240 employees, SILS carries out internationally high-quality life science research and provides education within various university programs. Research is also carried out in close cooperation with the medical, biotech, chemical, flavor, food & agricultural, and high-tech industries, and revolves around 4 main themes, Cell & Systems biology, Neurosciences, Microbiology and Green Life Sciences.
Want to know more about our organisation? Read more about
working at the University of Amsterdam.
Any questions? Do you have any questions or do you require additional information? Please contact:
T: +31 20 525 5519
Job application If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We accept applications until and including 6 November 2024.
Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
- a detailed CV including the months (not just years) when referring to your education and work experience;
- a letter of motivation;
- the names and email addresses of two references who can provide letters of recommendation.
At the time of recruitment, it is a requirement of the Marie Skłodowska-Curie Network program that PhD candidates have not been awarded a doctorate degree and are in the first 4 years (full-time equivalent) of their research careers. Furthermore, at the time of selection by the UvA, researchers must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 3 years immediately prior to their recruitment. Short stays, such as holidays, are not taken into account.
A knowledge security check can be part of the selection procedure.
(for details:
national knowledge security guidelines)
Only complete applications received within the response period via the link below will be considered.
The interviews will be held in the second half of November 2024.
The UvA is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.