Your role will be to implement and validate new methods and algorithms for molecular dynamics, Monte Carlo, optimization, and related techniques for both conventional and machine-learning force field and DFT simulations. You will also be involved in preparing scientific case studies to be published in leading scientific journals and providing tutorials for our end users.
The tasks require extensive experience with atomic-scale modeling and molecular dynamics, ideally with expertise in materials modelling, batteries, or polymers, good communication skills, and programming experience. Experience with machine-learning force fields is a plus. Current team members have a degree in theoretical physics, computer science or chemistry.
We are looking for talented individuals with strong competences in the areas:
- Personal experience with molecular dynamics and force field methods
- Strong general background in condensed matter physics and chemistry
- Excellent written and oral communication skills in English
- Good programming skills, in particular in Python and C++
The successful applicant
- Is an outstanding individual with strong competences in programming or atomic-scale modelling
- Has a broad set of skills and is ready to apply them to whatever task assigned
- Is dedicated with focus on getting the job done without sacrificing quality
- Is a team player
- Enjoys communicating and helping other people
- Has a positive mindset and is motivated by challenging projects
- Is self-motivated and takes responsibility and initiative
Apply for job
To view the job application please visit sjobs.brassring.com.