Driving data generation and analysis for ML-based molecule design - Inceptive

At Inceptive, you will drive development forward that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software.

There are more RNA sequences coding for a single target protein than atoms in the universe. Each of these RNA sequences differs in ways that may radically affect how it performs when used in medicine. Faced with this search space, we believe that machine learning based approaches are ideally placed to tackle the RNA design problem that we work on at Inceptive.

You will be responsible for designing, testing, and scaling novel experimental protocols to characterize molecules both in vitro and in silico. You will be responsible for deriving insights from our experimental data and enabling these to drive the future development of our models and our protocols. You will work effectively in an agile setting with recurring status updates and continuous knowledge sharing. We are happy to consider candidates at various stages in their career and the position could be tailored to your experience and career preferences.

Your mission, should you choose to accept it

• Analyze, visualize, and communicate insights from our experimental data
• Develop robust experimental protocols to further our ability to model RNA
• Build tools and pipelines to ensure the quality of the data that we generate
• Work together with a diverse team to incorporate insights from experimental design, machine learning, and molecular biology into our protocols and models
• Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise
• Collaborate with team members from diverse backgrounds to build innovative and scalable experiments to solve complex problems that span biology and computation

Qualifications

• Solid understanding of the principles of statistical data analysis and experimental design

• Confident computational skills (ideally Python) for doing practical statistical analysis

• Ability to communicate statistical information to a diverse audience

• Understanding of best engineering practices around reproducibility and versioning

• Eagerness to find creative solutions to complex problems and take end-to-end responsibility for their execution

• Availability to accommodate working with team members across different time zones, with one or two meetings per week starting at 8am PT or finishing at 7pm CET

• Readiness to travel several times a year for company retreats and business events

• We value the benefits of in-person collaboration and prefer candidates who can easily and regularly connect at our office in Palo Alto

• Ability to communicate technical and scientific concepts to team members from a broad variety of backgrounds

• Deep knowledge in your area of expertise with a strong eagerness to connect with and apply your skills in other areas

Preferred Qualifications

• Experience of the whole life-cycle of experimental protocol design
• Experience with high-throughput sequencing data or other biological data sources
• Experience with code-review and the use of a shared code repository
• Knowledge of an adjacent scientific field (molecular biology, genetics, immunology, chemistry)
• Familiarity with data visualization tools
• Familiarity with Cloud computing infrastructure

Compensation

$135K – $240K + Bonus + Equity