Senior Scientist/Principal Scientist, Protein Design & Modeling

Raven (RA Ventures)•Boston, MA

7h•$150,000 - $1,900,000

About The Position

We are seeking a highly skilled computational protein scientist to execute complex protein design and modeling work across our portfolio. Working closely with our scientific leadership and experimental teams, you will take defined research strategies and run with them independently — translating approaches into rigorous computational workflows and delivering high-quality results with minimal oversight. This role offers a rare breadth of impact: you will work hands-on with existing portfolio companies on active therapeutic programs, while also contributing to the formation of entirely new companies built on our computational protein design platform.

Requirements

A PhD scientist with 5+ years of industry experience in computational protein design and/or modeling.
Deeply grounded in structural biology, with hands-on expertise in protein structure analysis, structure-guided design, and the mechanistic reasoning that connects sequence and structure to function.
Broadly experienced across diverse protein types — enzymes, therapeutic antibodies, miniproteins, multi-domain proteins — and able to draw on that range to make sound design decisions across novel contexts.
A self-directed executor who can take a defined approach and run with it: managing your own workflow, troubleshooting independently, and delivering high-quality results without close supervision.
Fluent in modern protein ML tools, including generative design (e.g., RFdiffusion, ProteinMPNN), structural modeling (e.g., AlphaFold2/3, Boltz), and functional prediction frameworks (pLMs).
Curious and current with the literature, proactively identifying and testing new computational methods with therapeutic relevance.
A collaborative team player who works effectively with scientists from diverse experimental and computational backgrounds.

Responsibilities

Hands-on execution of complex protein design projects with high autonomy, translating defined scientific strategies into concrete computational approaches and driving them through to completion independently.
Apply deep expertise in structural biology to guide protein engineering decisions, leveraging mechanistic insight into protein folds, interfaces, conformational dynamics, and structure–function relationships.
Draw on broad experience across diverse protein modalities — including enzymes, antibodies and antibody fragments, miniproteins, and multi-domain scaffolds — to tackle a wide range of therapeutic design challenges.
Deploy the full spectrum of contemporary protein design and modeling tools, spanning biophysics-based methods, AI/ML generative models, and evolutionary approaches.
Couple computational methods with wet lab platforms to implement active learning systems for rapid protein development and iterative refinement.
Design protein libraries for hit identification and dataset generation to train and improve AI/ML models, as well as inform future development.
Build robust, reproducible pipelines for protein modeling and design across diverse functions and properties.
Partner effectively with scientific and experimental teams to move programs forward efficiently.
Contribute to the creation of next-generation portfolio companies built on computational protein design capabilities.