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Computational Research Scientist, Deep Learning

Manus Bio

Manus Bio

Waltham, MA, USA
Posted on Tuesday, June 18, 2024

Manus works across industries and value chains to accelerate the transition to Bio Alternatives – 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 Bio’s R&D team contributing to deep learning and AI tool development to create better enzymes, microbes, and bioprocesses to produce more sustainable Bio Alternative 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
  • Drive the development of digital infrastructure, including web UI development and data pipeline development, to support computational bioengineering
  • 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 0-5 years of experience and 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.