The Principal Scientist, In Silico Research & Modeling serves as Coriolis' leading expert in computational sciences, molecular modeling, and simulation technologies supporting drug product development. The position drives the evaluation, development, and implementation of advanced in silico methodologies to accelerate scientific innovation, strengthen Coriolis' service portfolio, and enable data-driven decision making across formulation development, process development, and product characterization. As a recognized scientific authority, the role identifies emerging computational technologies and translates them into practical applications that create competitive advantages for Coriolis and its clients. The position holder drives scientific initiatives at the interface of molecular modeling, biophysics, AI/ML, and digital sciences while establishing Coriolis as a thought leader in the application of computational approaches to biologics and advanced therapeutics. Scientific Leadership & Innovation Define and drive Coriolis' scientific strategy for in silico research and modeling technologies. Lead the evaluation and implementation of novel computational methodologies relevant to biopharmaceutical development. Serve as the internal scientific authority for molecular modeling, simulation, and data-driven predictive technologies. Identify emerging technologies and assess their applicability to Coriolis' scientific strategy and service offerings. Drive high-impact research initiatives and collaborations that expand Coriolis' capabilities and competitive positioning. Establish scientific roadmaps for future digital and computational service offerings. In Silico Research & Modeling Develop and apply advanced molecular modeling and simulation approaches to support drug product development. Lead computational investigations of protein stability, aggregation, conformational dynamics, formulation behavior, and molecular interactions. Design and execute molecular dynamics (MD) simulations and related computational workflows. Utilize advanced modeling approaches including: Atomistic Molecular Dynamics Coarse-Grained Simulations Enhanced Sampling Methods Brownian Dynamics Multiscale Modeling Molecular Docking Free Energy Calculations AI/ML-Assisted Modeling Develop predictive models supporting formulation optimization and developability assessments. Translate computational insights into actionable recommendations for development teams and clients. Portfolio Development & Business Impact Identify opportunities to expand Coriolis' service portfolio through computational and digital solutions. Create novel consulting and service offerings around in silico formulation development and modeling. Support strategic business development initiatives through scientific expertise and client-facing engagements. Contribute to proposal development and scientific discussions with prospective clients. Evaluate potential partnerships with software providers, technology companies, academic groups, and research consortia. Cross-Functional Collaboration Collaborate closely with Formulation Development, Analytical Development, Process Development, and Process Analytics teams. Drive integration of computational approaches into laboratory workflows and client programs. Facilitate knowledge transfer and adoption of modeling technologies across Coriolis. Act as scientific authority for complex client projects requiring advanced computational expertise. External Scientific Leadership Publish scientific findings and contribute to advancing the state-of-the-art in computational biopharmaceutical sciences. Establish and maintain collaborations with leading academic institutions and industry partners. Build Coriolis' external reputation in digital and computational drug product development. Represent Coriolis at scientific conferences, industry forums, and expert networks. Mentorship & Capability Building Mentor scientists and technical experts in computational methodologies. Build organizational capabilities in modeling, simulation, and data science. Promote scientific excellence and innovation through training and knowledge sharing. PhD in Computational Biophysics, Biophysics, Computational Chemistry, Molecular Modeling, Physical Chemistry, Bioengineering, Biotechnology, Pharmaceutical Sciences, Physics, or a related field. Minimum 10+ years of relevant industrial and/or academic experience in computational life sciences. Recognized expert in Molecular Dynamics and advanced computational modeling with demonstrated impact on biopharmaceutical development programs Demonstrated track record of applying computational approaches to biologics, protein science, vaccines, gene therapies, or related modalities. Experience driving scientific innovation and translating research into practical applications. Established scientific reputation demonstrated through publications, patents, conference presentations, or recognized industry contributions. Deep expertise in Molecular Dynamics (MD) simulations. Strong knowledge of protein structure, stability, aggregation, and molecular interactions. Experience with computational biophysics and molecular modeling methodologies. Strong programming skills (Python, R, or similar). Experience with high-performance computing environments. Preferred: AI/ML applications in molecular sciences. Protein language models and generative AI approaches. AlphaFold and structure prediction technologies. Schrödinger, GROMACS, AMBER, NAMD, OpenMM, Rosetta, or equivalent platforms. Statistical thermodynamics and free-energy methods. Digital twins and mechanistic modeling. Formulation modeling and developability prediction. Multiscale modeling approaches.