# (Associate) Scientist Protein Engineering and Molecular Modeling
We are seeking a skilled researcher specializing in protein engineering and molecular modeling to join dsm-firmenich's Computational Biotechnology team. In this role, you will model and optimize enzymes to support the development of innovative, sustainable bioproduction processes and specialty enzymes. You will translate structure-function insights into practical protein engineering strategies, from biodiversity exploration to library design. Working in multidisciplinary teams, you will collaborate closely with experts to scale molecular insights into real-world applications.
## Key Responsibilities
- Shape projects in collaboration with business partners, translating objectives into clear and actionable experimental plans
- Model protein structures to uncover structure-function relationships and design targeted mutant or diversity libraries
- Analyze, interpret, and communicate results effectively to stakeholders through reports and presentations
- Develop and apply machine learning and protein AI models to predict and improve structure-function outcomes
- Contribute to best practices and shared computational tools within the global data science and life sciences community
- Collaborate with cross-functional teams globally while applying modern software and ML practices, including Python and coding tools, to drive project success
## Required Qualifications
- PhD (or equivalent) in Biochemistry, Biophysical Chemistry, Bioinformatics, or Computer Science, with a focus on protein engineering and in silico design
- 2-4 years of experience in protein engineering and molecular modeling, applying modern data-driven approaches in areas such as metabolic engineering, enzymes, or biocatalysis
- Strong ability to quickly understand diverse proteins and enzymes, leveraging literature and data sources to assess scientific and business relevance
- Proven experience with bioinformatics and protein modeling tools (e.g., Rosetta, Schrödinger, Yasara) and databases such as UniProt, PDB, KEGG, or BRENDA
- Proficiency in Python and modern computational practices, with experience in ML tools, code management, and working in Unix/Linux environments; exposure to advanced simulations or protein AI tools is a plus
- Excellent problem-solving, collaboration, and communication skills, with a demonstrated track record of innovation and impact