Computational Research Scientist – Molecular Simulation & Peptide Design

vVARDIS; Michigan; On-site; USD 120,000 - 180,000; Full time

Job summary

vVARDIS, a Swiss-based oral health company, operates a Michigan dental materials research laboratory and is building an in-house computational capability to accelerate peptide design. As a Computational Research Scientist, you will be a founding member guiding the molecular-simulation component of a closed-loop platform.

You will work at the interface of computation and bench, collaborating daily with experimental teams to design a tight design–simulate–synthesize–test loop and help lay the

Qualifications

• PhD in computational chemistry, biophysics, chemical engineering, or a related field.
• Hands-on biomolecular molecular dynamics with peer-reviewed publications.
• Direct experience simulating peptide or protein self-assembly is strongly preferred.

Responsibilities

• Build and run the molecular-simulation pipeline that proposes and ranks novel oligopeptide sequences.
• Develop force-field parameterizations and simulation protocols as needed.
• Curate and steward a structured dataset linking peptide sequence to measured properties; document successes and failures.
• Contribute to platform architecture and integration of ML approaches for multi-objective sequence optimization.
• Communicate methods and findings clearly to a multidisciplinary team and mentor junior scientists.

Job description

vVARDIS is a Swiss-based oral health company founded by Dr. Haley and Dr. Goly Abivardi, dentists, innovators, and award-winning entrepreneurs. vVARDIS is the result of a combined 30 years of dental and entrepreneurial experience, and 20 years of laboratory and clinical research paired with the creative vision of its founders. At vVARDIS, we are committed to delivering innovative solutions that enhance oral health and well-being, inspired by the vision of our founders to foster preventive rather than reparative dentistry. Scientifically proven in over 200 publications, our unique technology can treat early caries, offering a noninvasive, pain-free solution for patients of all ages. We offer a number of oral health products targeting dental professionals and their patients, as well as consumers, all based on our proprietary technology. We value our people and believe in fostering a positive and collaborative work environment, based on our core values of innovation, excellence, integrity, and empathy. We are located in Zug, Switzerland, with operations in Europe and the U.S. Join us on this exciting journey!

About the Role

vVARDIS is building an in-house computational capability to accelerate the design of the next generation of functional peptides that build on the science behind our proprietary technology. As a Computational Research Scientist, you will be a founding member of this effort and will drive the molecular‑simulation half of a closed‑loop, computationally guided peptide‑design platform. Your models will propose and prioritize novel oligopeptide sequences with tailored physicochemical properties, which are then synthesized and tested experimentally, with the resulting data feeding back to sharpen the next design cycle.

Based at our Michigan dental materials research laboratory and working closely with the parent‑company R&D group in Zug, Switzerland, you will sit at the interface between computation and the bench. You will collaborate daily with our experimental team to design a tight design–simulate–synthesize–test loop and help lay the scientific and technical foundations of a platform we intend to grow over the coming years. We are open to discussing hybrid arrangements and level/title commensurate with experience for an exceptional candidate.

Responsibilities

• Build and run the molecular‑simulation pipeline that proposes and ranks novel oligopeptide sequences against multiple target physicochemical and functional properties relevant to our platform.
• Develop force‑field parameterizations and simulation protocols as needed.
• Curate and steward a structured, high‑quality dataset linking peptide sequence to measured physicochemical and mineralization behavior, recording both successes and failures; this dataset is the long‑term foundation of the design platform.
• Contribute to platform architecture and, over time, to the integration of machine‑learning and active‑learning approaches (e.g., protein/peptide models, generative sequence design, Bayesian optimization) for multi‑objective sequence optimization.
• Communicate methods and findings clearly to a multidisciplinary team, help shape scientific direction and tooling choices, and mentor junior scientists as the team grows.

Qualifications

• PhD in computational chemistry, physical chemistry, biophysics, chemical engineering, or a related field.
• A demonstrated, hands‑on track record in biomolecular molecular dynamics, evidenced by peer‑reviewed publications.
• Direct experience simulating peptide or protein self‑assembly is strongly preferred; a background in a relevant biomolecular self‑assembly research group is ideal.

Required Skills

• 3+ years of hands‑on molecular dynamics expertise with at least one standard engine (e.g., GROMACS, AMBER, OpenMM, NAMD, CHARMM, etc.).
• 2+ years of coarse‑grained molecular dynamics for self‑assembly (Martini / martinize2 or equivalent), including model setup, adaptation, and validation.
• Strong scientific programming and workflow automation (Python, Bash) in a Linux / high‑performance‑computing environment.
• A solid grasp of peptide and protein biophysics and the physical chemistry of self‑assembly, electrostatics, and pH effects.
• 3+ years of project management experience of collaboration with multidisciplinary teams in a leadership role
• Aptitude and willingness to acquire additional specialized simulation methods on the job
• Working familiarity with biophysical characterization (CD spectroscopy, ThT fluorescence, TEM/AFM, CMC / tensiometry) to help bridge computation and experiment.
• Excellent communication skills, with the ability to explain complex computational concepts to experimental scientists and non‑specialists.

Preferred Skills

• Free‑energy and enhanced‑sampling methods (e.g., FEP, umbrella sampling, metadynamics).
• Constant‑pH molecular dynamics and pKa / protonation‑state modeling.
• Experience modeling peptide interactions with mineral surfaces (e.g., hydroxyapatite or calcium phosphate) and the associated force fields.
• Force‑field parameterization for non‑standard or novel chemistry.
• Machine learning for molecular systems: protein/peptide language models, generative sequence design, and active learning / Bayesian optimization.
• Familiarity with commercial modeling suites (e.g., Schrödinger) alongside open‑source tools.
• Scientific curiosity and a passion for solving complex molecular design challenges.

Equal Opportunity Statement

vVARDIS is an equal opportunity employer. All aspects of employment, including hiring, promotion, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate based on race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.