About the role

Aplyr's Quick Take

This role is for a Materials Science Applications Scientist who will provide scientific support to customers using advanced computational methods. You'll be involved in presentations, training, and collaborating with both customers and internal teams to solve complex materials science problems. It's primarily an individual contributor role with some collaborative elements.

Good fit

Ideal candidates will have a PhD in a relevant field and experience with molecular modeling and simulations. Strong communication skills and a passion for helping others solve scientific challenges are essential.

Worth noting

The role involves significant customer interaction and travel, which may not suit everyone. Additionally, there's an emphasis on publishing and presenting research, which could be a plus for those looking to build their academic profile.

We’re seeking Materials Science Applications Scientists to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods.

Schrödinger is a science and technology leader with over 30 years of experience providing solutions for atomic-scale modeling and physics-based chemical simulations. As part of our European Materials Science Applications Science team, you’ll work closely with our industrial and academic customers and help solve challenging scientific problems.

Who will love this job:

A computer-aided materials science enthusiast (both in theory and application) who has solid experience in design and analysis of materials based on atomistic simulations
An excellent communicator and presenter with superb organizational skills
A dedicated scientist interested in advancing materials science research
A creative collaborator who enjoys helping others solve problems
A self-motivated team player who can also conduct independent research

What you’ll do:

Provide scientific support to current and prospective customers, which includes scientific presentations; giving demonstrations of our materials science modelling platform; training; and working with customers to enable them to solve challenging scientific and engineering problems
Act as a critical link between our customers and Schrödinger software developers, Sales, and Marketing by providing feedback on technology requirements, feature enhancements, and use-case scenarios
Publish scientific papers and present at conferences

What you should have:

PhD in Chemistry, Materials Science, Chemical Engineering, Physics, or a related field
Broad knowledge of molecular modeling theory and applications; extensive experience with classical molecular dynamics simulations of complex materials systems (e.g., polymers, soft matter, or structured solutions)
Enthusiasm for traveling to meetings at customer sites
Excellent English language skills (both verbal and written)

Preferred skills and background:

Experience with applying coarse-grained and/or quantum mechanical modeling techniques in materials science research
Familiarity with modern machine learning techniques for materials science
Experience in the commercial sector
Python programming proficiency

Our benefits include local transport reimbursement, a BahnCard 50, our Employee Equity Plan, the EGYM Wellpass (corporate fitness program), bike leasing, an employee volunteer program, our donation match program, access to the corporate benefits platform, a dedicated counseling service, and our travel insurance.

When you’re in the office you can profit from our central location, the charging of personal devices with green energy, stocked kitchens with coffee/tea, fruit, snacks, and beverages, and the organization of team-building and social events.

Sound exciting? Apply today and join us!

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.

Skills & Tags

python machine learning ai ios product design marketing sales

Aplyr's read

Schrödinger leverages computational modeling to innovate in drug discovery and materials science, attracting scientists and tech experts passionate about cutting-edge research.
Synthesized from recent postings & public sources

What's promising

•Schrödinger is at the forefront of computational drug discovery, offering significant innovation potential.
•The company provides a collaborative environment for scientists and technologists to solve complex problems.
•Schrödinger's global presence allows for diverse career opportunities across various scientific and technical roles.

What to watch

•High reliance on computational methods may limit applicability in some real-world scenarios.
•The niche focus on modeling requires specialized skills, potentially narrowing job applicant pools.
•Rapid technological changes in biotech could outpace Schrödinger's current capabilities.

Why Schrödinger

•Schrödinger integrates advanced computational techniques with traditional scientific methods.
•The company's dual focus on drug discovery and materials science is relatively rare in the industry.
•Schrödinger's software solutions are pivotal in reducing time and cost in the R&D process.

Aplyr’s read is generated by AI from public sources. Was it useful?