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RASyn - (Senior) Scientist, Computational Biology


Cambridge, MA, US
  • Job Type: Full-Time
  • Function: Research Sci/Assoc/Mgr
  • Industry: Life Science
  • Post Date: 11/27/2023
  • Website:
  • 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

RASyn, a new biotechnology company launched by RA Capital, is building a proprietary platform of innovative technologies to transform the discovery and development of breakthrough therapeutic, diagnostic, and industrial products. RASyn’s platform integrates computational protein design and engineering, machine learning, synthetic biology, and single cell sequencing and will enable cheaper, faster, and larger scale production and optimization of biologics, enzymes, and biomolecule libraries. We are assembling a diverse team of the most talented scientists and innovators who seek to invent the future today and have a passion for solving the most intractable problems.

About RA Capital:

RA Capital 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:

RASyn is seeking an innovative, self-motivated, and team-oriented (Senior) Scientist in Computational Biology, with a passion for developing analysis methods to derive insight from multi-modal high-dimensional data. In your role, you will develop and deploy a range of computational methods across multiple modes of experimental output, with a focus on large scale single-cell multi-omics data sets for novel target discovery and immune profiling. You will work closely with our cross-functional teams and be a key contributor supporting our R&D programs. As a member of a rapidly growing and very engaged team, you will have the opportunity to participate in leading cutting-edge research and development, and work with a highly skilled multidisciplinary team in a fast-paced startup environment.

Key Responsibilities:

  • Develop data analysis strategies and deploy computational tools for the analysis of high-throughput single-cell multi-omic experimental data
  • Develop and apply statistical tools and machine learning models, and integrate multimodal and multiomic data to improve these models
  • Develop bioinformatic pipelines to support research programs, including mining of public databases (e.g TCGA, Encode, GEO and other relevant repositories)
  • Analyze and communicate data analysis verbally and in writing
  • Work closely with wet lab scientists on experimental design, data quality assessment, analysis, and integration with computational pipelines

Qualifications & Skills:

  • PhD in computational biology, bioinformatics, computer science, or a related field and 2+ years relevant experience, pharmaceutical or biotech preferred
  • Experience with analysis of next-generation sequencing (NGS) data and building end-to-end analysis pipelines for various types of NGS experiments
  • Experience with single-cell sequencing data analysis (e.g scRNA-seq), and machine learning for single-cell data analysis
  • Proficiency in Python, R, and/or other programming languages (e.g C++) as well as version control systems (git)
  • Experience with cloud computing (AWS) and Linux-based operating systems
  • Expertise in conducting novel, quantitative analysis as part of research and discovery
  • Strong interpersonal skills, with the ability to build strong working relationships with cross-functional teams
  • Strong analytical skills, with attention to detail and ability to multitask in a fast-paced startup environment
  • Experience with computational protein design is a plus