Three PHD
Four-year PhD in the ML-GUIDE consortium to develop ML-guided directed evolution frameworks.
Design accelerated Design-Build-Test-Learn cycles and apply active learning for model-guided evolution.
Requires an MSc in (bio)chemistry, biotechnology, computational chemistry, synthetic chemistry/biology, or a related field.
Omschrijving
Three fully funded, four-year doctoral positions to combine directed evolution of diverse biomolecules with deep learning approaches, aiming to develop improved biocatalysts and therapeutics. Within the ML-GUIDE project you will build a first-class framework to expedite the design of high-affinity binders or efficient (bio)catalysts by merging directed evolution, next-generation sequencing, and deep learning. The work focuses on establishing accelerated Design-Build-Test-Learn cycles and applying active learning to continuously improve models and guide evolutionary trajectories toward promising but otherwise inaccessible sequence spaces. You will be embedded in one of the ML-GUIDE research groups and concentrate on engineering a particular biomolecule and its associated function.
Functie eisen
- MSc degree (or equivalent university degree) in (bio)chemistry, biotechnology, computational chemistry, synthetic chemistry/biology, or a related field.
- Experience in one or more of the following areas is highly preferred: directed evolution, molecular machine learning, next-generation sequencing, or synthetic chemistry.
- Interest in working as part of a highly interdisciplinary team at the interface of synthetic biology, molecular machine learning, and synthetic chemistry.
- Research-oriented attitude with good analytical skills.
- Excellent communication and organizational skills.
Taken
- Develop a framework to expedite the design of high-affinity binders and efficient (bio)catalysts.
- Integrate directed evolution experiments with next-generation sequencing and deep learning approaches.
- Establish and run accelerated Design-Build-Test-Learn (DBTL) cycles.
- Implement active learning strategies to continuously improve predictive models.
- Guide evolutionary trajectories toward promising regions of sequence space.
- Collaborate with researchers across the consortium to support engineering efforts for a specific biomolecule.
Werkomstandigheden
- Four-year doctoral appointment (typical structure: 1 year + 3 years).
- Flexible working arrangements: option to adjust working hours in exchange for corresponding free hours.
- End-of-year bonus and a holiday allowance provided as percentage allowances.
- Extensive opportunities for personal and professional development.
Beschrijving van de organisatie
The positions are embedded in an interdisciplinary, collaborative research project (ML-GUIDE) that combines directed evolution, next-generation sequencing, and deep learning to make directed evolution guidable and predictable. Host institutions are research universities with broad teaching and research portfolios spanning chemistry, biology, artificial intelligence, and engineering. These institutions emphasize interdisciplinary research, collaboration with industry and societal partners, and an open international academic community. Appointments are situated within research institutes focused on molecular chemistry, complex molecular systems, and AI-enabled molecular design.