Apprenticeship

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.

The Inceptive Apprenticeship is a 1-year full-time research training program for early-career individuals who are motivated to learn, excited to break down traditional disciplinary boundaries, and passionate about exploring the frontiers of AI and biology.

Training is not limited to one discipline or another, and Apprentices are actively encouraged to collaborate and learn broadly. We are building the foundation for people who are experts in what we do — the antedisciplinary Inceptive Beginner’s mindset.

The 2024–2025 Apprenticeship program will be the second year that Inceptive is hosting the program, and will build off the successes and feedback from the 2023–2024 cohort of Apprentices.

Interested? Applications will close on February 4th, 2024 and interviews will begin in February. Contact us at hiring@inceptive.team for more information.

What the program looks like:

• 1-year full-time research experience with one-on-one mentorship and hands-on wet lab and computational training, starting in August 2024.
  • 1-month intensive bootcamp spanning topics across development; 5 months working with a mentor as an individual contributor in a project; 6 months working as a cohort on an Apprenticeship project, driving all areas from project initiation to execution.
• Opportunity to hone research skills and kick start your career while working on problems that can make a direct impact on RNA therapeutics and human health.
• Career development opportunities including journal clubs, conferences, fireside chats, quarterly international company retreats, and networking opportunities with industry professionals (including founders, scientists, engineers, operations experts, entrepreneurs).

Your mission, should you choose to accept it

• 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 design, plan, and execute innovative and scalable experiments to solve complex problems that span biology and machine learning
• Explore RNA biology and therapeutics with high-throughput assays, next-generation sequencing, lab automation, in vitro functional assays, and mammalian cell culture
• Explore analyzing and modeling biological data with deep learning and generative models
• Learn and develop expertise in a variety of machine learning, laboratory instrumentation, computational biology, bioinformatics, and high-throughput biology techniques
• Analyze and communicate data to colleagues across all roles and levels
• Learn from members of a humble, dynamic, and highly communicative team

Qualifications

If you don't recognize yourself here, see our other posting for those with a background in Machine Learning or similar.

• Completed Bachelor’s degree in a relevant field (e.g., Biochemistry, Molecular Biology, Biophysics, Genetics, Microbiology, Engineering, Computer Science, Chemistry, Physics, Mathematics) by summer 2024
• Familiarity with basic molecular biology, cell biology, and/or biochemistry laboratory techniques, with a strong eagerness to connect and apply your skills in other areas
• Eagerness to find creative solutions to complex problems and take end-to-end responsibility of its execution
• Ability to communicate technical and scientific concepts to team members from a broad variety of backgrounds
• 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
• Candidates with traditionally underrepresented backgrounds and experiences are highly encouraged to apply

Compensation

$100K – $108K

Salary : $105,000