Associate Scientist - Bioinformatics V
Associate Scientist - Bioinformatics V
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Job Description
Job Title: Bioinformatics Engineer In Silico Antibody Design
12 months contract Onsite at Foster City CA
We are seeking a Bioinformatics Engineer with specialized expertise in in silico antibody design to lead the development of an AIfirst platform transforming the future of antibodybased drug discovery. This pivotal role requires an innovative and proactive individual with deep experience in bioinformatics machine learning and largescale biological data particularly in antibody design and optimization. The ideal candidate will be responsible for building scalable AIdriven solutions that accelerate the identification validation and development of therapeutic antibodies.
Key Responsibilities:
Develop AIDriven 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 largescale data processing storage and computation ensuring the scalability of antibody design pipelines.
Apply StateoftheArt AI Techniques for Antibody Discovery: Innovate with cuttingedge AI methods including diffusion models and neural networks to refine antibody sequences and explore vast design spaces for novel therapeutic candidates.
Collaborate on Antibody Drug Discovery: Work with crossfunctional 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.
Minimum Qualifications:
Educational Background: PhD in Bioinformatics Computational Biology Computer Science or a related field with demonstrated expertise in antibody design.
Machine Learning Expertise: Solid experience applying AI and machine learning frameworks to biologics particularly antibody data.
Programming Proficiency: Proficient in Python R and experience with bioinformatics libraries (e.g. Biopython PyMOL) with strong skills in cloudbased deployment of machine learning applications.
Experience with Antibody Datasets: Demonstrated expertise in handling antibody sequence and structural data and applying machine learning to improve therapeutic properties such as affinity specificity and stability.
Preferred Skills:
Data Handling Expertise for Antibody Design: Extensive experience in curating harmonizing and preprocessing largescale antibody datasets including highthroughput screening data and structural models.
Understanding of Antibody Data Nuances: Deep understanding of antibody sequencestructure relationships developability challenges and immunogenicity risks with an ability to integrate these insights into data workflows.
Advanced AI Methods for Antibody Engineering: Experience with AIdriven 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.
Collaboration and Communication: Proven ability to collaborate in agile interdisciplinary teams and communicate effectively across scientific and technical domains.
Passion for Innovation in Antibody Therapeutics: A passion for driving the next generation of antibody therapeutics through AI accelerating drug discovery timelines and improving clinical outcomes.
Employment Type
Full Time
