Computational Biologist
Valthos Inc.
Valthos is an applied biological intelligence company. We build and deploy software and biological AI systems to safeguard humanity.
The same AI architectures that enable self-driving cars, land rockets with precision, and deliver expert-level reasoning are beginning to be deployed in biological design. To stay ahead, we must advance our arsenal of tools to capture and design against real-time sensitivities in nature’s evolving mutational landscape.
We are a group of mission-driven software engineers from Palantir and applied biological ML engineers from MIT’s Broad Institute and DeepMind making the latest advances in computational biology accessible in the real-world for federal and commercial use.
We are seeking a highly skilled Computational Biologist to bridge machine learning and biology by building robust data and evaluation frameworks for assessing and responding to biological threats, and for rapidly designing precision biologics.
The Role
Contribute to shaping and executing the Valthos-wide research and development roadmap
Identify large-scale biological datasets appropriate for training frontier biological models, and build workflows and infrastructure for processing these datasets
Design, build, and apply evaluation frameworks for rigorously assessing model performance on real-world problems in biological security
Design wet-lab experiments to evaluate the efficacy and real-world utility of designed biologics
Collaborate closely with AI engineers to design and train models tailored to tasks in biological security and precision biologics
Collaborate closely with software engineers to build and deploy tools for data analysis, including proper documentation and testing
Visualize and communicate results clearly within Valthos and externally
Work with customers and external collaborators to understand their needs and effectively represent Valthos
Embrace continuous learning in both technical and non-technical areas across Valthos
Stay up-to-date on state-of-the-art methods at the intersection of AI and biology
Qualifications (required)
Experience analyzing biological datasets, ideally sequence-based modalities (e.g., genomic, protein, metagenomic)
Experience planning and running in silico computational biology experiments
High proficiency in Python and its scientific package ecosystem
Experience with bioinformatics sequence analysis tools (e.g., aligners)
Experience with cloud computing platforms (e.g., AWS)
Qualifications (preferred)
Proven ability to design, implement, and evaluate novel methods in computational biology
Experience working with experimental biologists to plan and interpret the results of wet-lab experiments
Experience with ML-centric bioinformatics and structure-based tools (e.g., AlphaFold)
Knowledge of biological databases (e.g., NCBI)
Experience with machine learning model training and evaluation
Contributions to open-source projects
If there is a fit, we'll schedule two technical interviews. The final step is an onsite in our office, where you'll work on a small project, discuss ideas, and work with the wider team.