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CradleCR

Scientific Education Developer, Cradle Academy

Cradle leverages AI to expedite protein engineering, enabling teams to generate better protein candidates faster while ensuring data privacy.

Cradle
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Cradle is a software platform for AI-guided discovery and optimization of proteins. We are looking for a Scientific Education Developer to create educational content and curriculum for our platform, enabling scientists to master protein engineering with AI.

Requirements

  • MSc or PhD in Structural / Molecular Biology, Bioinformatics or a related field
  • 3-5+ years of experience creating educational content or technical training in life sciences, biotech, or scientific software
  • Basic proficiency in data analysis using Python and relevant data science libraries (pandas, scikit, scipy, matplotlib, etc.)

Benefits

  • Competitive salary
  • Generous equity stake in the company
  • Wide range of benefits and career progression opportunities

About the job

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Posted on

Job type

Full Time

Experience level

Mid-level

Location requirements

Hiring timezones

Netherlands +/- 0 hours, and 1 other timezone

About Cradle

Learn more about Cradle and their company culture.

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Cradle is at the forefront of protein engineering and AI technology, allowing scientific teams to engineer proteins faster and more efficiently. With a focus on leveraging AI, Cradle generates protein candidates and enhances their properties, resulting in more breakthroughs with fewer experimental rounds. This process is guided by the user's own experimental data, empowering teams to streamline their workflows significantly.

Companies such as Novo Nordisk, Johnson & Johnson, and IFF leverage Cradle's innovative platform to achieve superior protein optimization. The AI-powered design tools enable users to craft highly effective solutions across various applications, including therapeutics, agricultural innovations, and food ingredient development. By ensuring private, secure access to experimental data, Cradle guarantees that only the authorized team can utilize their proprietary information without any risk of data being used to train models for other organizations, giving them full control over their intellectual property.

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