Company Description

As one of the leading automotive suppliers worldwide, we develop solutions to fulfill people´s dreams of mobility on a daily basis. Driver safety, sustainability and industrialization of future technology are just some of our key fields where we already make a meaningful difference in the everyday life of people. Knowing our technology helps to make the world a better and safer place is what drives us.

Job Description

Key Targets of the Job:

Develop and optimize computational workflows integrating quantum simulations, molecular descriptors, and predictive machine learning modelsApply advanced cheminformatics and data-driven approaches for virtual screening, property prediction, and reaction mechanism analysisDesign and implement automated pipelines for high-throughput quantum chemical calculations and machine learning model trainingModel and simulate complex chemical reaction mechanisms across diverse environments using quantum mechanical and ML-assisted approachesAnalyze simulation results to extract molecular-level insights and support experimental design or product developmentConduct comprehensive literature reviews and generate high-quality technical documentation, reports, and presentationsCollaborate effectively within an interdisciplinary team of computational scientists, chemists, physicists, and materials engineersSupport external collaborations, joint research projects, and technology scouting initiativesDemonstrate a willingness to travel occasionally for project meetings, conferences, and collaborative activities

QualificationsPhD in quantum chemistry, computational chemistry, cheminformatics, materials science, physics, or a closely related field (mandatory academic background)Proven hands-on experience with quantum chemistry methods (e.g., DFT, ab initio) and related software (e.g., Gaussian, ORCA, VASP, CP2K, DMol³)Strong background in cheminformatics, including experience with molecular representations and libraries such as RDKit and Open BabelDemonstrated ability to incorporate machine learning (e.g., scikit-learn, PyTorch, TensorFlow) into computational chemistry workflows Experience in modeling reaction mechanisms, energy landscapes, or catalytic processes at the atomic or molecular level - good to have Proficiency in Python (preferred), along with experience using scientific computing libraries such as NumPy, pandas, and ASEFamiliarity with molecular dynamics tools (e.g., GROMACS, LAMMPS) is a plusPostdoctoral or several years of industrial experience in the field is highly preferredExcellent written and spoken English communication skills, with the ability to articulate complex technical concepts to diverse audiencesStrong analytical thinking, creativity, and a proactive, solution-oriented approach to problem solvingAbility to work independently and collaboratively within cross-functional and interdisciplinary teamsPortuguese languages skills  written and spoken is a plus

Additional Information

▪ Integration in a challenging and international work environment, featured by the existence of state-of-the-art technologies
▪ Local employment contract with attractive remuneration package and benefits
▪ Continuous professional training and excellent possibilities of personal and professional development

Ready to drive with Continental? Take the first step and fill in the online application.