Synolo - Senior/Principal Scientist, AI/ML Aided Protein Design and In Silico Antibody Optimization
RAVen
Cambridge, MA, US
- Job Type: Full-Time
- Function: Research Sci/Assoc/Mgr
- Industry: Life Science
- Post Date: 12/04/2023
- Website: www.racap.com/venture
- Company Address: 200 Berkeley Street, 18th Floor, Boston, MA, 02116
About RAVen
RAVen (RA Ventures) is the venture-focused arm of RA Capital Management, LP, a Boston-based biotechnology and life sciences investment firm.Job Description
Synolo Therapeutics, an early-stage biotechnology company launched by RA Capital, is pioneering the development of precision-targeted immunotherapies for cancer. Powered by computational protein design and proprietary technologies yielding biological data sets at unprecedented scale and resolution, we are building a pipeline of first-in-class multi-specific biologics with novel functionalities. Synolo was founded by pioneers in the fields of protein design and engineering, synthetic biology, DNA sequencing, immunology, and biologics drug discovery and development.
About RA Capital:
RA Capital Management funds and builds healthcare and life science companies using an evidence-based investment approach informed by TechAtlas, a think tank within RA Capital which analyzes scientific and clinical data from academic literature and industry sources to anticipate how breakthroughs might impact industry stakeholders, physicians, patients, and policymakers. TechAtlas' analyses are captured in a unique collection of competitive landscapes, or ‘maps’, that identify competitive therapeutics, diagnostics, research tools, and/or technological capabilities in a given area.
About the Role:
Synolo Therapeutics is seeking an innovative, self-motivated, and team-oriented Senior/Principal Scientist in artificial intelligence/machine learning (AI/ML)-aided protein design and in silico antibody optimization. An ideal candidate has a passion for discovering and developing novel medicines, and thrives working in a fast-paced startup team. This position is key to executing the core mission of Synolo: utilizing computational protein design and in silico antibody lead optimization at scale to accelerate the discovery of novel precision targeted multi-specific biologics therapeutics.
About RA Capital:
RA Capital Management funds and builds healthcare and life science companies using an evidence-based investment approach informed by TechAtlas, a think tank within RA Capital which analyzes scientific and clinical data from academic literature and industry sources to anticipate how breakthroughs might impact industry stakeholders, physicians, patients, and policymakers. TechAtlas' analyses are captured in a unique collection of competitive landscapes, or ‘maps’, that identify competitive therapeutics, diagnostics, research tools, and/or technological capabilities in a given area.
About the Role:
Synolo Therapeutics is seeking an innovative, self-motivated, and team-oriented Senior/Principal Scientist in artificial intelligence/machine learning (AI/ML)-aided protein design and in silico antibody optimization. An ideal candidate has a passion for discovering and developing novel medicines, and thrives working in a fast-paced startup team. This position is key to executing the core mission of Synolo: utilizing computational protein design and in silico antibody lead optimization at scale to accelerate the discovery of novel precision targeted multi-specific biologics therapeutics.
In this role, you will contribute to building and managing in-house capabilities for AI/ML aided protein design and in silico optimization of multi-specific antibody drug candidates. You will support our cross-functional teams with your deep knowledge of computational protein design and in silico antibody optimization and be a key contributor to our drug discovery and development programs. As a member of a rapidly growing and highly engaged team, you will help us in our mission to develop novel therapeutics to improve patients’ lives.
Key Responsibilities:
- Work with the team to build and evolve the biologics drug discovery platform
- Research, analyze, and implement best practices (computational protein design by AI/ML, machine learning operations)
- Collaborate with the cross functional drug discovery team to identify and resolve drug discovery bottlenecks using state-of-the-art tools
- Conceptualize, implement, validate, and deploy AI/ML tools and modules and integrate them into the platform
- Extract and prepare drug discovery data from public or internal repositories, collaborate with external data providers; use the data to train, deploy, and update machine learning models, and build pipelines to automate processes
- Build and apply AI/ML models for the design of smart antibody display libraries, protein structure prediction, affinity modeling, de novo design, antibody/antigen binding modeling, antibody thermostability and chemical stability modeling, aggregation, selectivity/poly reactivity, immunogenicity modeling, etc.
- Quantify and benchmark model performance, proactively address performance gaps, and deliver validated, top-performing models
Qualifications & Skills:
- PhD or equivalent and at least 3 years of experience in computational protein design, computer science, data science, antibody bioinformatics, or other STEM disciplines with a strong emphasis on AI/ML and in silico antibody modeling. Level is commensurate with prior experience
- Strong programing skills with Python, familiar with software development lifecycle models
- Hands-on experience with RosettaFold, RFdiffusion, AlphaFold, or ESMFold,
- Hands on experience is PyMol, MOL or equivalent
- Hands-on experience in designing smart antibody display libraries, protein structure prediction, affinity modeling, de novo design, antibody/antigen binding modeling, antibody thermostability and chemical stability modeling, aggregation, selectivity/poly reactivity, immunogenicity modeling, etc.
- Familiar with multiple frameworks, toolkits, and packages
- Strong problem-solving and excellent communication (verbal and written) skills
- Open minded, willing to learn, and able to learn on the fly
- Past productive collaboration with people of diverse technical backgrounds
- Nice to have: cloud computing and experience in biotech/pharma industry etc.