Job Description

Scientist, Hybrid Computational / Synthetic Biology Join to apply for the Scientist, Hybrid Computational / Synthetic Biology role at Manifold Bio Scientist, Hybrid Computational / Synthetic Biology Join to apply for the Scientist, Hybrid Computational / Synthetic Biology role at Manifold Bio Get AI-powered advice on this job and more exclusive features. Manifold Bio is a dynamic biotech company building a pipeline of targeted biologics using a novel in vivo-centric discovery approach. 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. Position We are seeking a hybrid scientist with a mix of wet and dry lab experience who is excited to go end-to-end designing, executing, and analyzing next-generation assay formats. With hybrid founders and a highly interdisciplinary team, we are strong believers in the synergy that comes from combining disciplines. You will design DNA libraries, use advanced cloning techniques to build them, devise novel screens, and then apply statistical analyses and machine learning approaches to your data. You will work closely with the CSO on a set of focused, highly impactful projects that advance the capabilities of our protein therapeutics discovery platform. Additionally, you will support analysis of the team’s NGS data, derive useful insights from these data, and advise on platform improvements and next steps. Individuals with experience in disease bioinformatics, machine learning, or protein engineering will have the opportunity to work in these respective budding areas of research at Manifold Bio. This position will be customized to fit the individual’s expertise and interests. Responsibilities Design, execute, interpret and iterate on novel library-based experiments Apply statistical methods and machine learning to NGS data to identify novel variants Provide deepful insightful analyses of team’s NGS experiments and advise on next steps Develop novel protein engineering platform technologies Desired Experience And Capabilities PhD or equivalent experience in protein and or molecular biology, biological engineering or a related field; must total 5+ years hands-on molecular biology wet lab experience and/or NGS data analysis experience Experience going end-to-end from experimental design through cloning, execution, NGS, and analysis Expertise in statistical computing and willingness to adapt our python / jupyter / git / AWS stack Collaborative, curious, flexible, and strong communication skills Why you might be a good fit Experience with screening-based methods with an NGS readout, e.g. DMS, MPRA, CRISPR screening, cancer screens, single cell sequencing Experience designing and assaying libraries of DNA, protein, gRNAs, promoter regions, etc. in multiplex Experience designing antibody or other therapeutic binder libraries Experience with phage/yeast/mammalian display or similar Experience predicting sequence-function relationships (e.g. using ML/biophysical models) 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. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Research, Analyst, and Information Technology Referrals increase your chances of interviewing at Manifold Bio by 2x Sign in to set job alerts for “Scientist” roles. 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