PhD Position in Machine Learning: Wageningen University & Research offers a fully funded PhD position focused on developing innovative machine learning methods for understanding protein-ligand interaction dynamics. This position emphasizes collaboration between computational techniques and wet-lab research, aiming to advance methodologies in the life sciences.
PhD Position in Machine Learning for Life Sciences
Designation
PhD Candidate in Machine Learning for Life Sciences
Research Area
- Machine Learning
- Computational Biology
- Protein-Ligand Interaction Dynamics
Location
Wageningen University & Research, Wageningen, Netherlands
Eligibility/Qualification
- Completed MSc degree in Computer Science, Computational Biology, Computational Chemistry, or a related field.
- Proven experience in programming with Python (or proficiency in C/C++ or Rust).
- Experience in molecular dynamics simulations is advantageous.
- Strong understanding of machine learning methodologies, particularly neural networks.
- Excellent English writing and communication skills (C1 level).
- A collaborative attitude and interest in interdisciplinary research.
Job Description
As a PhD student, the successful candidate will:
- Develop new machine learning methodologies applicable to life sciences, focusing on protein-ligand interaction dynamics.
- Synthesize and evaluate recent research in machine learning, chemistry, and biology at the intersection of these fields.
- Collaborate with national and international researchers.
- Publish and present research findings in esteemed journals and conferences.
The position comes with a gross salary starting from €2,901 per month, increasing to €3,707 by the fourth year, along with excellent employment benefits including parental leave, flexible working hours, and a pension scheme.
How to Apply
Interested candidates should apply directly through the vacancy page on the Wageningen University & Research website by clicking the apply button.
Last Date for Apply
Applications will be accepted until April 28, 2025.
