Computational Research Scientist, Enzyme Engineering

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 enzyme engineering challenges and other biological problems. This candidate should have experience in enzyme engineering and exposure to deep learning methodologies. This person will play an integral part of the Manus R&D team contributing to deep learning and AI tool development to create better enzymes, microbes, and bioprocesses to produce sustainable BioAlternative products.

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.

Responsibilities:

• Develop predictive models for enzyme engineering using machine-learning/deep-learning techniques
• Leverage in-house enzyme engineering data to enhance machine-learning/deep-learning models
• Develop and implement computational approaches using 3D structures and/or sequences as input to increase enzyme stability, solubility and activity
• Assist with maintenance of hardware and software 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, ideally with a focus on AI driven techniques and deep learning
• Proven experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries.
• Proficiency in programming languages such as Python, R, or MATLAB
• Experience using computational tools to improve enzyme activity and/or specificity
• Excellent communication skills, both written and verbal

Preferred qualifications:

• Knowledge of protein structural modeling and prediction
• Experience in industrial biotechnology or a related industry
• Experience building and optimizing deep learning architectures, transformers and diffusion-based models.
• Background in enzyme catalysis and reaction mechanisms.

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.