Apex Systems
Computational Biologist – Obesity Research
Boston, MA ($138,000.00-$224,400.00) 2 weeks ago
This range is provided by Apex Systems. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $110,000.00/yr - $125,000.00/yr
Job Description A fast‑paced biotech team is seeking a Computational Biologist to lead bioinformatics efforts in antibody discovery and engineering. This role is ideal for someone who thrives at the intersection of data science and molecular biology, and is excited to contribute to the development of novel biologics.
Key Responsibilities
Analyze genomic and RNA‑Seq datasets from public repositories to identify new therapeutic targets
Oversee external efforts to verify gene sequences not yet available in public databases
Lead development of intuitive databases housing antibody repertoire sequences
Design and implement streamlined data entry workflows in Benchling for improved organization and accessibility
Apply in‑silico design strategies and software tools to remediate antibody sequence liabilities and enhance biophysical properties
Support external collaborations focused on machine learning applications in antibody discovery
Curate and integrate relevant genomic and transcriptomic datasets
Analyze antibody libraries using clustering methods such as clonotyping and sequence‑based grouping
Skills & Experience
Deep understanding of machine learning approaches for protein design and biological data analysis
Proven experience implementing bioinformatics tools for managing and analyzing large datasets (e.g., NGS, antibody libraries)
Proficient in Python or R, with experience using libraries like Biopython and PyMOL
Skilled in DNA and RNA sequencing data analysis
Familiarity with molecular modeling tools such as Rosetta, Schrodinger, or MOE
Strong background in antibody engineering, including liability remediation and biophysical optimization
Excellent communicator and collaborator, comfortable in cross‑functional teams
Adaptable and effective in a fast‑paced, small‑team environment
Qualifications
Ph.D. in Bioinformatics, Computational Biology, Statistics, or Biological Sciences with 0–5 years of experience
MS in a relevant field with 10–15 years of experience and demonstrated expertise
Equal Employment Opportunity / EEO Statement Stratacuity is an Equal Employment Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stratacuity will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.
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This range is provided by Apex Systems. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $110,000.00/yr - $125,000.00/yr
Job Description A fast‑paced biotech team is seeking a Computational Biologist to lead bioinformatics efforts in antibody discovery and engineering. This role is ideal for someone who thrives at the intersection of data science and molecular biology, and is excited to contribute to the development of novel biologics.
Key Responsibilities
Analyze genomic and RNA‑Seq datasets from public repositories to identify new therapeutic targets
Oversee external efforts to verify gene sequences not yet available in public databases
Lead development of intuitive databases housing antibody repertoire sequences
Design and implement streamlined data entry workflows in Benchling for improved organization and accessibility
Apply in‑silico design strategies and software tools to remediate antibody sequence liabilities and enhance biophysical properties
Support external collaborations focused on machine learning applications in antibody discovery
Curate and integrate relevant genomic and transcriptomic datasets
Analyze antibody libraries using clustering methods such as clonotyping and sequence‑based grouping
Skills & Experience
Deep understanding of machine learning approaches for protein design and biological data analysis
Proven experience implementing bioinformatics tools for managing and analyzing large datasets (e.g., NGS, antibody libraries)
Proficient in Python or R, with experience using libraries like Biopython and PyMOL
Skilled in DNA and RNA sequencing data analysis
Familiarity with molecular modeling tools such as Rosetta, Schrodinger, or MOE
Strong background in antibody engineering, including liability remediation and biophysical optimization
Excellent communicator and collaborator, comfortable in cross‑functional teams
Adaptable and effective in a fast‑paced, small‑team environment
Qualifications
Ph.D. in Bioinformatics, Computational Biology, Statistics, or Biological Sciences with 0–5 years of experience
MS in a relevant field with 10–15 years of experience and demonstrated expertise
Equal Employment Opportunity / EEO Statement Stratacuity is an Equal Employment Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stratacuity will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.
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