Member of Technical Staff - Computational Biologist

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.

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.