Scientist – Hybrid Computational / Synthetic Biology

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)