PhD Position in Machine Learning to Predict Enzyme Specificity

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:

• Develop machine learning methodology to integrate docking results with protein sequence-and structure-features to predict enzyme specificity.
• Incorporate predicted protein dynamics as input for enzyme specificity prediction.
• 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.