Graduate Intern for Deep Learning in Protein Design Boston, Massachusetts, United States, Full-Time
Position Summary
Manus works across industries and value chains to accelerate the transition to BioAlternatives – better performing and more sustainable versions of complex molecules traditionally sourced from plants, animals, or fossil fuels. Our platform is proven to work across scales, bridging the Valley of Death between lab and manufacturing more efficiently and more reliably to deliver the benefits of synthetic biology today.
We are seeking a Graduate Intern in Deep Learning for Protein Design to investigate key gaps in AI-guided protein engineering and explore novel approaches to address them. The ideal candidate has experience applying deep learning methods to biological problems, such as protein sequence design, structure prediction, or mutation effect modeling. This internship offers the opportunity to work at the intersection of machine learning and synthetic biology, contributing directly to scalable, real-world applications.
Why Work At Manus
Opportunity – For motivated, results-oriented team members, our growth creates opportunities for personal and professional advancement.
Accountability – You are given the resources you need to succeed and the freedom to make it happen; in return, we hold each other accountable for our high expectations.
Passion – We love what we do and enjoy working with others who feel the same way. We embrace the challenge and hard work that comes with working on the cutting edge.
Key Responsibilities
Evaluating state-of-the-art deep learning models for mutation effect prediction and identify their limitations (eg. Epistasis, protein dynamics, etc)
Drive exploratory research into potential avenues to fill gaps in DL-based approaches
Communicate results and insights to multidisciplinary teams, including presentations and written reports
Required Qualifications
Currently enrolled in a Masters or PhD program in Computer Science or BioEngineering or similar programs with emphasis on AI applications in Biological systems
Demonstrated experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries.
Proficiency in programming languages such as Python and familiarity with AI-assisted coding tools (eg., Claude Code, Codex)
Excellent verbal and written communication skills
Preferred Qualifications
Familiarity with protein engineering (eg. Directed evolution, ML/AI-led)
Familiarity with protein language models and similar transformer-based models
Familiarity with benchmarking techniques and public datasets for protein sequence to function relationship
Experience in industrial biotechnology or a related industry
Preferred Working Style
Must be very well-organized and be able to handle multiple projects simultaneously.
Must be a quick learner who is self-motivated and able to ask questions and seek clarity.
Must be flexible with day-to-day duties and able to thrive in a start-up environment.
Must be an excellent team member with strong communication skills and a desire to work collaboratively.
Must hold themselves to the highest professional, scientific and ethical standards.
