­­­­­­­­Bioinformatics Engineer - The Fountain Group

The Fountain Group is currently seeking a ­­­­­­­­Bioinformatics Engineer for a prominent client of ours. This position is located in ­­Foster City, CA. Details for the position are as follows:

Job Description:

**HYBRID ROLE (3 days onsite, 2 days remote)**

• We are seeking a Bioinformatics Engineer with specialized expertise in in silico antibody design to lead the development of an AI-first platform, transforming the future of antibody-based drug discovery.
• This pivotal role requires an innovative and proactive individual with deep experience in bioinformatics, machine learning, and large-scale biological data, particularly in antibody design and optimization.
• The ideal candidate will be responsible for building scalable AI-driven solutions that accelerate the identification, validation, and development of therapeutic antibodies.
• Key Responsibilities:
  • Develop AI-Driven Antibody Design Ecosystems: Design and build advanced platforms to drive in silico antibody design and optimization, supporting rapid and efficient therapeutic discovery.
  • Implement Scalable Antibody Prediction Models: Architect machine learning models specifically tailored for antibody sequence and structure predictions, leveraging deep learning to predict binding affinities, structural stability, and therapeutic potential.
  • Leverage Cloud Platforms for Antibody Data Processing: Utilize modern cloud platforms for large-scale data processing, storage, and computation, ensuring the scalability of antibody design pipelines.
  • Apply State-of-the-Art AI Techniques for Antibody Discovery: Innovate with cutting-edge AI methods, including diffusion models and neural networks, to refine antibody sequences and explore vast design spaces for Client therapeutic candidates.
  • Collaborate on Antibody Drug Discovery: Work with cross-functional scientific teams to integrate data from immunology, structural biology, and bioinformatics into actionable insights for antibody discovery and optimization.
  • Continuously Integrate Emerging Technologies: Stay ahead of AI and bioinformatics advancements, continuously refining and expanding in silico methods for antibody engineering and drug discovery.

Qualifications:

• Required:
  • PhD in bioinformatics / computational biology / computational science or related field
  • Antibody design experience
  • Machine learning expertise (applying AI and machine learning to biologics and antibody data)
  • Python & R Programming
  • Biopython or pymol (or other bioinformatics library experience)
  • Cloud based deployment of machine learning apps
• Preferred:
  • Data Handling Expertise for Antibody Design: Extensive experience in curating, harmonizing, and preprocessing large-scale antibody datasets, including high-throughput screening data and structural models
  • Understanding of Antibody Data Nuances: Deep understanding of antibody sequence-structure relationships, developability challenges, and immunogenicity risks, with an ability to integrate these insights into data workflows
  • Advanced AI Methods for Antibody Engineering: Experience with AI-driven techniques such as inverse folding, generative models, and structural docking to guide antibody design and optimization
  • Analytical and Strategic Skills: Strong analytical abilities to extract actionable insights from complex antibody datasets, with a focus on developing innovative therapeutic strategies

Compensation: $56-66 per hour depending on experience