Remote Molecular Biologist for AI Target Verification

Mercor; New York (NY); Remote; USD 55,000 - 110,000; Part time

Job summary

Mercor partners with a leading AI research organization to verify protein target assignments in large-scale bioactivity databases. You will review primary literature and apply scientific judgment to determine whether UniProt IDs reflect the proteins studied, feeding AI drug discovery pipelines.

You will read papers and patents, flag errors, and propose correct UniProt accessions while documenting concise evidence-based notes for each case. Remote, part-time engagement in the U.S. market.

Qualifications

• BA/BS with 5+ years, MS with 2+ years, or PhD in pharmacology/biochemistry/molecular biology/chemical biology.
• Hands-on binding or functional assay experience (SPR, TR-FRET, radioligand binding, kinase assays, GPCR).
• Currently bench-active in a research, scientist, or associate scientist role.
• Working fluency with UniProt workflows and related bioactivity pipelines.

Responsibilities

• Read primary sources (papers, patents) to verify protein target assignments against UniProt records.
• Flag and classify target assignment errors using a structured taxonomy.
• Propose correct UniProt accessions where assignments are wrong.
• Write concise, evidence-grounded notes explaining your reasoning.

Skills

Scientific reasoning

Literature analysis

Bioactivity databases knowledge

Education

BA/BS with 5+ years, MS with 2+ years, or PhD in pharmacology/biochemistry/molecular biology/chemical biology

Hands-on binding or functional assay experience (SPR, TR-FRET, radioligand binding, kinase assays, GPCR)

Currently bench-active in a research, scientist, or associate scientist role

Working fluency with UniProt workflows

Tools

UniProt workflows

ChEMBL

BindingDB

PubChem

Job description

Mercor partners with a leading AI research organization to verify protein target assignments in large-scale bioactivity databases. You will review primary literature and apply scientific judgment to determine whether UniProt IDs reflect the proteins studied, feeding AI drug discovery pipelines.

You will read papers and patents, flag errors, and propose correct UniProt accessions while documenting concise evidence-based notes for each case. Remote, part-time engagement in the U.S. market.