As Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE), we aim to educate and train the next generation of data scientists during their doctoral thesis in close contact to domain-specific knowledge and research in three application domains: Life and medical science, earth science, energy systems and material science. Visit HDS-LEE at: https://www.hds-lee.de/
This HDS-LEE PhD position will be located at the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich. The JSC operates supercomputers of the highest performance class, enabling scientists and engineers in Germany and Europe to tackle some of the most complex and challenging problems of our time.
We are looking to recruit a
PhD Position - Data-Driven Approaches to Rational Designs of Covalent Drugs
The rational development of covalent inhibitors has been steadily increasing in the past decades. Numerous warheads have been developed, expanding the covalent warhead toolbox and allowing for selective targeting of specific amino acid residues. Covalent compounds are on the market or in advanced clinical trials. As more data emerge regarding safety and efficacy of covalent drugs, the structure-guided optimization and rational development needs to be improved. The PhD project aims at developing data driven models for the optimization of covalent docking procedures.
- Generation of training dataset by extraction of covalent complexes from different sources
- Model development for the protein ligand complexes structure by using generative adversarial neural networks or alternatively a Monte-Carlo sampling of the conformational space with a further refinement using a Convolutional Neural Network (CNN). Additionally, multiple machine learning models may be used for scoring of obtained structures.
- Validation of the model by using experimental data set of e.g. SARS-CoV2 Mpro cysteine protease
- Embedding of the model: implementation of the geometrical-features-driven model and energetic features in the scoring step
- You have a high interest to apply your data science knowledge to life science
- M. Sc. degree physics, chemistry, molecular biology, applied mathematics or computer science
- Experience with UNIX-like operating systems
- Mathematical and programming skills (Python, Machine Learning)
- Basic understanding of molecular forces and structures
- Excellent knowledge of written and oral English (TOEFL or equivalent evidence)
- Interactive person with good communication skills
- Used to work in international teams
- Ideal prior knowledge on MD simulations
- High level of scholarship as indicated by bachelor and master study transcripts and two reference letters.
We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! This HDS-LEE PhD position will be located at Forschungszentrum Jülich. We offer ideal conditions for you to complete your doctoral degree:
- Outstanding scientific and technical infrastructure - ideal conditions for successfully completing a doctoral degree
- A highly motivated group as well as an international and interdisciplinary working environment
- Continuous scientific mentoring by your scientific advisors
- Chance of participating in (international) conferences
- Unique HDS-LEE graduate school program
- Qualification that is highly welcome in industry
- Further development of your personal strengths, e.g. via a comprehensive further training programa structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs
Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.
We also welcome applications from disabled persons.