Computational Biologist

About Us

An early stage, well-funded biotech start-up focused on advancing cutting-edge therapeutic gene editing technologies is seeking a passionate and driven Computational Biologist to join a team of experienced founders and industry experts. In this role, you will be a part of a multidisciplinary team driving breakthroughs and innovation, playing a meaningful role in the execution of ambitious goals and our development roadmap, delivering important impact to the world of drug discovery. Come and be part of our open, collaborative and entrepreneurial culture.   

• Design and implement computational models and algorithms to enhance genome editing techniques.
• Analyze genomic data to identify and profile potential targets for gene editing and optimize editing strategies.
• Collaborate with wet-lab scientists to validate computational predictions and integrate experimental data.
• Utilize bioinformatics tools and software to analyze large-scale genomic datasets.
• Develop pipelines for data processing, analysis, and visualization.
• Interpret results and present findings to the team and stakeholders.
• Collaborate with software, AI, and biology team members to ensure high-quality and timely delivery of features.
• Communicate complex technical information effectively to both technical and non-technical audiences.

• Deep understanding of genomic data and analysis methods
• Excellent interpersonal and communication skills, with the ability to work effectively across multidisciplinary teams.
• Strong analytical and critical thinking skills, with a proven track record of addressing complex scientific challenges.
• Ability to work on ambiguous problems while defining goals & targets for them. 

• Ph.D. in Computational Biology, Bioinformatics or a related field.
• 2+ years of industry/postdoc experience in computational Biology, Genetics or Bioinformatics. Alternatively, published high-impact papers in peer-reviewed journals. 
• Experience with high-throughput sequencing data and genomic data analysis. 
• Proficiency in programming languages such as Python.
• Experience with bioinformatics tools and databases, ML tools and frameworks for biology, statistical methods for genomic data analysis.
• Familiarity with CRISPR/Cas systems and other genome editing technologies.
• (Optional) Experience in any of: large scale deep learning, generative models, graph neural network, deep learning for drug discovery, large language models.
• Excellent oral and written communication skills.