The job, in the employer's words
This role is for one of our clients
Compensation: $50-$70 per hour
Join an exciting AI-driven research initiative focused on improving the accuracy of protein target annotations used in large-scale bioactivity databases. In this role, you will apply your expertise in molecular biology, pharmacology, biochemistry, or chemical biology to validate protein target assignments through primary scientific literature review. Your work will directly contribute to enhancing high-quality datasets that power next-generation AI models for drug discovery and life sciences research.
Requirements
Key Responsibilities
- Review scientific publications, patents, and other primary literature to verify protein target assignments against UniProt records.
- Evaluate the accuracy of protein annotations in large-scale bioactivity databases using scientific evidence.
- Identify, categorize, and document incorrect target assignments using established validation guidelines.
- Recommend the correct UniProt accession numbers where annotation discrepancies are identified.
- Prepare concise, evidence-based summaries that clearly explain scientific reasoning and validation decisions.
- Collaborate with research teams to improve the quality and reliability of biological datasets used in AI applications.
Required Qualifications
- One of the following:
- Bachelor's degree with 5+ years of relevant industry experience.
- Master's degree with 2+ years of relevant industry experience.
- PhD with research or industry experience in biotechnology, pharmaceutical sciences, or drug discovery.
- Educational background in Pharmacology, Biochemistry, Molecular Biology, Chemical Biology, or a closely related life sciences discipline.
- Hands-on experience with binding or functional assays such as:
- SPR (Surface Plasmon Resonance)
- TR-FRET
- Radioligand Binding Assays
- Kinase Assays
- GPCR Functional Assays
- IC50, Ki, or KD measurements
- Currently working in a laboratory or research environment as a Scientist, Associate Scientist, or equivalent research role.
- Practical experience using UniProt or related workflows supporting:
- Structure–Activity Relationship (SAR)
- High-Throughput Screening (HTS)
- Target Validation
- Biochemical Profiling
- IND-Enabling Research
Preferred Qualifications
- Experience working with bioactivity databases such as ChEMBL, BindingDB, or PubChem.
- Knowledge of selectivity profiling and counterscreening methodologies.
- Understanding of pharmacological distinctions such as agonists vs. antagonists and activators vs. inhibitors.
- Strong literature review, analytical reasoning, and scientific documentation skills.
- Excellent written communication with exceptional attention to detail.
Engagement Details
- Remote independent contractor opportunity.
- Immediate start available.
- Expected commitment of 10–20 hours per week.
- Initial engagement of 1–2 months, with the possibility of extension based on project needs and performance.
- Open to professionals currently based in the United States.
Contract & Payment Terms
- This is an independent contractor position.
- Work can be completed remotely with a flexible schedule.
- Project duration may be extended, shortened, or concluded based on business requirements and individual performance.
- The role does not require access to confidential or proprietary information from any current or previous employer.
- Payments are processed weekly through supported international payment platforms based on approved work completed.
Equal Opportunity
We are committed to providing equal opportunities to all qualified applicants and making reasonable accommodations throughout the hiring process upon request.
Benefits mentioned
- Join an exciting AI-driven research initiative focused on improving the accuracy of protein target annotations used in large-scale bioactivity databases. In this role, you will apply your expertise in molecular biology, pharmacology, biochemistry, or chemical biology to validate protein target assignments through primary scientific literature review. Your work will directly contribute to enhancing high-quality datasets that power next-generation AI models for drug discovery and life sciences research.
Requirements mentioned
- One of the following:
- Educational background in Pharmacology, Biochemistry, Molecular Biology, Chemical Biology, or a closely related life sciences discipline.
- Hands-on experience with binding or functional assays such as:
- Currently working in a laboratory or research environment as a Scientist, Associate Scientist, or equivalent research role.
- Practical experience using UniProt or related workflows supporting:
- Experience working with bioactivity databases such as ChEMBL, BindingDB, or PubChem.
- Knowledge of selectivity profiling and counterscreening methodologies.
- Understanding of pharmacological distinctions such as agonists vs. antagonists and activators vs. inhibitors.
- Strong literature review, analytical reasoning, and scientific documentation skills.
- Excellent written communication with exceptional attention to detail.
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