What are the responsibilities and job description for the Computational Research Scientist, Deep Learning position at Manus?
Computational Research Scientist, Deep Learning
Manus
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 motivated individual for a Computational Research Scientist position
that will specialize in deep learning to solve biological problems. This candidate should have experience
in at least one area of deep learning but have familiarity with a broad array of techniques, such as data
pipeline development, metabolic engineering, or protein engineering. This person will play an integral
part of Manus Bios R&D team contributing to deep learning and AI tool development to create better
enzymes, microbes, and bioprocesses to produce more sustainable BioAlternative products.
Why work at Manus Bio:
- 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 come with working on the cutting edge.
Responsibilities:
- Develop and implement deep learning models to predict and optimize enzymes and metabolic pathways in microbial systems.
- Conduct simulations and modeling of metabolic networks to identify key regulatory nodes and potential engineering targets.
- Perform protein variant designs with established protocols to support in-house projects.
- Collaborate with experimental biologists to design and interpret experiments that validate computational predictions.
- Communicate results and insights to multidisciplinary teams, including presentations and written reports.
Required qualifications:
- Ph.D. in Bioengineering, Biochemistry, Biostatistics, Chemical Engineering, Computer Science, or similar discipline, with a strong focus on deep learning and/or cell engineering
- Proven experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries.
- Proficiency in programming languages such as Python, R, or MATLAB
- Excellent communication skills, both written and verbal
Preferred qualifications:
- Familiarity with metabolic engineering and synthetic biology principles
- Knowledge of metabolic flux analysis and constraint-based modeling (e.g., FBA, COBRA toolbox)
- Knowledge of protein structural modeling and prediction
- 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.
