Biologist with Python Proficiency - AI Trainer - Remote

We're building a talent pool of Biology professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models. Designed for biology specialists who enjoy deep technical problem-solving, this pipeline role is for those looking to apply their computational expertise to evaluate and push the boundaries of frontier AI models, relying on domain-specific tools such as NEURON, Brian2, OpenSim, AMICI, or MNE-Python, with verifiable, code-graded answers run inside isolated Linux environments. Key Responsibilities Identify an appropriate computational biology package and build problems whose solution genuinely hinges on that tool's core capabilities, whether biophysical models, ODE/PDE systems, biomechanical formulations, or sequence algorithms. Develop full Python solutions for each problem, providing all necessary input files, model definitions, and network configurations as required. Establish the correct numerical output and define how close the AI model needs to get, using tolerance values appropriate to the biological context. Run the problem against the AI model across multiple parallel attempts, analyzing where it succeeds or falls short, and adjusting difficulty until the pass rate falls between 10% and 30%. Tune channel kinetics, stimulation protocols, and solver tolerances iteratively, building an understanding of how the model navigates complex neuronal, biomechanical, and systems biology problems. Hand off completed tasks to a senior reviewer in your subfield and refine based on their feedback before final submission. Core Requirements Academic background in Biology or a closely related field. At least 2 years of hands-on experience in biology research, applied work, or teaching. Solid Python skills, applied to writing and validating computational solutions. Capacity to build problems that cannot be solved without specialized computational biology software. Excellent written and verbal communication skills in English. Ability to work independently in a remote, fast-paced environment. Nice-to-Have Working knowledge of one or more domain-specific computational biology tools, including but not limited to NEURON, Brian2, NEST, OpenSim, AMICI, libroadrunner, MNE-Python, or Biopython, or a demonstrated ability to get up to speed independently. Prior exposure to how frontier AI models approach complex simulation tasks. Knowledge spanning more than one biology domain, such as computational neuroscience, biomechanics, or systems biology. Familiarity with containerized or sandboxed Linux execution environments. The icing on the Kake: 💵 Competitive Pay in USD – Work globally, get paid globally. 🏡 Fully Remote – Simply put, we trust you. 🌱 Better Me Fund – We invest in your personal growth and passions. ❤️ Compassion is Badass – Join a community that invests in social good. Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

Identify computational biology packages and build problems that leverage their core capabilities. Develop Python solutions, analyze AI model performance, and refine tasks based on feedback.

Candidates should have an academic background in Biology or a related field and at least 2 years of experience in biology research or teaching. Solid Python skills and the ability to work independently in a remote environment are essential.

• Competitive Pay • Fully Remote • Better Me Fund • Community Investment in Social Good

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Biology
• Python
• Computational Biology
• Problem Solving
• Communication
• Research
• Teaching
• Numerical Analysis
• Modeling
• Simulation
• Neuroscience
• Biomechanics
• Systems Biology
• Linux
• AI Development

• Science & Research
• Technology
• Education

Formation minimale

Baccalauréat

Expérience minimale

2+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level