Scientist / Senior Scientist, Library-guided Protein Engineering

Manifold Bio is a biotech company pursuing a pipeline of protein therapeutics using novel molecular measurement technologies and library-guided protein engineering. Our drug discovery engine is differentiated by massively parallel screening in vivo from the beginning of our discovery process. This unique platform is powered by a proprietary protein barcoding technology that allows multiplexed protein quantitation at unprecedented scale and sensitivity. We combine this and other high-throughput protein engineering approaches with computational design to create antibody-like drugs and other biologics. Our world-class team of protein engineers, biologists, and computational scientists are working together to aim the platform at therapeutic opportunities where precise targeting is the key to overcoming clinical challenges. 

The Role

Manifold Bio is seeking an exceptional scientist with deep library-based engineering experience to join our platform team. You will play a key role in the pursuit of innovations that further expand the scale and capability of Manifold Bio’s platform, including our M-Codes technology for multiplexed tracking of therapeutics. The role involves collaborating closely with our drug programs team to leverage M-Codes for in vivo multiplexing and to innovate on protein therapeutic modalities and designs. You will work closely with the CSO and a team of creative experimental, computational, and hybrid scientists to design and execute experiments applying high-throughput protein engineering and synthetic biology principles. Central to this work will be developing new assays and design, construction, and high-throughput screening of complex protein libraries. We’re a growing team and there is substantial opportunity for growing into leadership over important R&D efforts. As a key member of our growing company, you will contribute to building a culture that embraces scientific boldness and a strong team-focused approach to solving problems.

What You’ll Do

• Advance the scale, sensitivity and robustness of our M-Code multiplexing technology by combining protein engineering, synthetic library design, directed evolution and in vitro display approaches.
• Work both independently and in collaboration with experimental, computational, and hybrid bioengineers to design, execute, analyze and interpret experiments.
• Coordinate and build efficient working relationships with the Programs, Protein Sciences and In Vivo Biology teams to support the deployment of M-Codes technologies for screening drug candidates
• Mentor junior scientists in developing skills essential to the execution of rigorous scientific research
• Ensure data generated is documented in a timely and organized fashion, and present ideas and results to colleagues and leadership

Who You Are

You love to tinker with biological parts and enjoy the challenge of troubleshooting en route to the development of a novel assay. You are passionate about combining both rational design and unbiased approaches in problem solving.

Requirements:

• PhD in Biochemistry, Bioengineering, Molecular Biology or related field.
• A proven track record executing high-throughput screens and/or protein/enzyme engineering work.
• Strong technical proficiency in key biochemistry/molecular biology techniques, including: cloning, protein purification and ELISA/Western analysis.
• Hands-on experience with NGS-based workflows
• Strong desire to work collaboratively within a fast-paced and multidisciplinary team environment.
• Detail-oriented with exceptional organizational and communication skills.
• Interest and experience mentoring junior scientists.
• Exceptionally self-motivated and scientifically curious

Nice to Have:

• 2+ years of Startup/Biotech/Pharma experience in protein engineering or assay development.
• Experience in either directed evolution or phage/yeast/mammalian or related display technologies.
• You are a “hybrid” scientist with computational experience or experience collaborating closely with computational scientists.
• Experience working with antibody or antibody-like molecules.

We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.