Bioinformatics Engineer for In Silico Antibody Design

4 weeks ago


San Mateo, California, United States Unicon Pharma Inc Full time
Job Title: Bioinformatics Engineer for In Silico Antibody Design

Job Summary:

Unicon Pharma Inc is seeking a highly skilled Bioinformatics Engineer to lead the development of an AI-first platform for in silico antibody design. This innovative role requires a deep understanding of bioinformatics, machine learning, and large-scale biological data, particularly in antibody design and optimization.

Key Responsibilities:

  • Design and build advanced platforms to drive in silico antibody design and optimization, supporting rapid and efficient therapeutic discovery.
  • Implement scalable antibody prediction models, leveraging deep learning to predict binding affinities, structural stability, and therapeutic potential.
  • Leverage 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, innovating with cutting-edge methods to refine antibody sequences and explore vast design spaces for novel therapeutic candidates.
  • Collaborate 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, staying ahead of AI and bioinformatics advancements to refine and expand in silico methods for antibody engineering and drug discovery.

Requirements:

  • PhD in Bioinformatics, Computational Biology, Computer Science, or a related field, with demonstrated expertise in antibody design.
  • Machine learning expertise, with solid experience applying AI and machine learning frameworks to biologics, particularly antibody data.
  • Programming proficiency in Python, R, and experience with bioinformatics libraries, with strong skills in cloud-based deployment of machine learning applications.
  • Experience with antibody datasets, including high-throughput screening data and structural models.


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