System One
Job Title:
Computational Biology Scientist, Antibody Engineering Location:
Rockville, MD (100% Onsite) Hours/Schedule:
Monday–Friday, 9:00 AM – 5:00 PM Compensation:
$45.00 – $70.00/hour Type:
Contract (6 months, extension possible but not guaranteed)
Overview Leading biotechnology organization focused on cancer therapeutics is seeking a Computational Biology Scientist, Antibody Engineering to support next-generation antibody discovery. This is a highly impactful, first-of-its-kind role within the organization, working at the intersection of structural biology, computational modeling, and AI-enabled protein engineering.
Responsibilities
Develop and apply computational methods to engineer monoclonal and bispecific antibodies (90% computational/10% bench work)
Integrate deep-learning and physics-based models for protein structure prediction and developability assessment
Analyze structural biology and NGS datasets to guide antibody library design and optimization
Build and maintain Python-based bioinformatics and machine learning workflows for data processing and modeling
Collaborate closely with experimental scientists to translate computational insights into actionable design decisions
Perform limited bench-based molecular biology work, including cloning and experimental support (up to 10%)
Requirements
Ph.D. in Structural Biology, Biochemistry, Biophysics, Protein Sciences, Computational Biology, Bioengineering, Machine Learning, Computer Science, or related field with 0–3 years postdoctoral experience OR Master’s degree with 5+ years of relevant industry experience
Strong background in structural biology, including peer-reviewed publications
Hands-on experience with protein modeling and structure prediction tools such as AlphaFold, RosettaFold, Schrödinger, MOE, or RFdiffusion
Advanced Python programming skills for data analysis, automation, and ML workflow integration
Experience with NGS data analysis and bioinformatics pipelines
Familiarity with AI/ML approaches in protein engineering preferred but not required if structural biology and Python expertise are strong
Ability to work effectively in highly collaborative, interdisciplinary research teams
Must be legally authorized to work in the United States for any employer
Benefits System One offers eligible employees health and welfare benefits coverage options, including medical, dental, vision, spending accounts, life insurance, voluntary plans, and participation in a 401(k) plan.
#J-18808-Ljbffr
Computational Biology Scientist, Antibody Engineering Location:
Rockville, MD (100% Onsite) Hours/Schedule:
Monday–Friday, 9:00 AM – 5:00 PM Compensation:
$45.00 – $70.00/hour Type:
Contract (6 months, extension possible but not guaranteed)
Overview Leading biotechnology organization focused on cancer therapeutics is seeking a Computational Biology Scientist, Antibody Engineering to support next-generation antibody discovery. This is a highly impactful, first-of-its-kind role within the organization, working at the intersection of structural biology, computational modeling, and AI-enabled protein engineering.
Responsibilities
Develop and apply computational methods to engineer monoclonal and bispecific antibodies (90% computational/10% bench work)
Integrate deep-learning and physics-based models for protein structure prediction and developability assessment
Analyze structural biology and NGS datasets to guide antibody library design and optimization
Build and maintain Python-based bioinformatics and machine learning workflows for data processing and modeling
Collaborate closely with experimental scientists to translate computational insights into actionable design decisions
Perform limited bench-based molecular biology work, including cloning and experimental support (up to 10%)
Requirements
Ph.D. in Structural Biology, Biochemistry, Biophysics, Protein Sciences, Computational Biology, Bioengineering, Machine Learning, Computer Science, or related field with 0–3 years postdoctoral experience OR Master’s degree with 5+ years of relevant industry experience
Strong background in structural biology, including peer-reviewed publications
Hands-on experience with protein modeling and structure prediction tools such as AlphaFold, RosettaFold, Schrödinger, MOE, or RFdiffusion
Advanced Python programming skills for data analysis, automation, and ML workflow integration
Experience with NGS data analysis and bioinformatics pipelines
Familiarity with AI/ML approaches in protein engineering preferred but not required if structural biology and Python expertise are strong
Ability to work effectively in highly collaborative, interdisciplinary research teams
Must be legally authorized to work in the United States for any employer
Benefits System One offers eligible employees health and welfare benefits coverage options, including medical, dental, vision, spending accounts, life insurance, voluntary plans, and participation in a 401(k) plan.
#J-18808-Ljbffr