Strong fit for computational materials scientists who build automated workflows and bridge algorithmic modeling with user interfaces.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Schrödinger via Greenhouse
Schrödinger, a science and technology leader with over 35 years of experience providing solutions for atomic-scale modeling and physics-based chemical simulations, is seeking a materials science developer to build advanced software tools and automated workflows for molecular reactivity and homogeneous catalysis.
We are seeking a scientific developer with a PhD (or Master’s degree with 5+ years of relevant experience) in Materials Science, Computational Chemistry, or Chemical Engineering, combining deep domain knowledge in density functional theory (DFT) reactivity with strong software engineering skills in Python to accelerate catalyst design and chemical process modeling.
Key Responsibilities
Design, build, and deploy automated Python based software workflows for molecular catalyst screening, transition state locator algorithms, and reaction network analysis.
Bridge materials modeling algorithms with intuitive user interfaces to streamline molecular property predictions and reactivity profiling.
Collaborate with multiple teams to integrate quantum mechanical calculation engines into broader materials science platforms.
Maintain high-quality, reusable software code bases and contribute to collaborative, production-grade toolsets.
Collaborate closely with teams based in the USA and globally on a daily basis.
Required Qualifications
PhD in Materials Science, Computational Chemistry, Chemical Engineering, or related field (or a Master’s degree with 5+ years of relevant industry/research experience).
Strong practical background in density functional theory (DFT) applied to reaction pathways, organometallic complexes, or molecular reactivity.
Experience utilizing standard electronic structure packages (e.g., Jaguar, Gaussian, ORCA, Q-Chem) within automated Python workflows.
Desirable Qualifications
Experience with reaction network generation, transition state modeling, or microkinetic simulation tools.
Familiarity with graphical user interface (GUI) development or building interactive computational workflows.
Exposure to machine learning/data science integration for molecular reactivity screening and automated workflows for biodegradability and environmental sustainability assessment.
Knowledge of microkinetic modeling modules for homogeneous catalysis and multi-scale chemical reaction engineering.
As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, or sexual orientation. To us, "diversity" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.
Source: Schrödinger careers (Greenhouse)