Pharmaceutical Research Scientist (Remote | $60–$90/hr)

Synthires; California; Remote; USD 83,000 - 124,000; Part time

Benefits offered by this job

Fully remote

Hourly contract engagement

Claude Max subscription reimbursed

Job summary

Synthires is seeking experienced Drug Discovery Scientists to design AI-driven research tasks for pharmaceutical R&D. You will craft realistic problems that require reasoning across incomplete and indirect evidence, using source-grounded data rooms and rigorous grading rubrics.

The role emphasizes distinguishing genuine scientific reasoning from pattern matching, with expert evaluation of AI outputs for quality and defensibility in a fully remote setting.

Qualifications

• PhD or equivalent in drug discovery, medicinal chemistry, chemical biology, biochemistry, or related field.
• Strong understanding of drug discovery methodologies and scientific evidence evaluation.
• Ability to construct complex scientific problems with defensible conclusions.
• Strong analytical and critical-thinking skills.
• Experience working in a remote research environment and committing to at least 20 hours per week.

Responsibilities

• Design challenging, realistic drug discovery research problems based on authentic scientific workflows.
• Develop scenarios where correct conclusions come from multiple pieces of evidence rather than direct statements.
• Build data rooms with real, source-grounded scientific data and documentation.
• Ensure every decisive scientific value and evidence can be traced to a reliable source.
• Create grading documents and evaluation rubrics to assess scientific reasoning and conclusions.
• Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility.
• Run verification and calibration processes for reproducibility and appropriate difficulty.
• Identify weaknesses in task design and revise accordingly.
• Provide expert judgment on scientific questions, task difficulty, and quality of AI reasoning.
• Collaborate with project reviewers and domain experts to refine research tasks.

Skills

Mechanistic enzymology

Structure-guided peptide design

Structure-guided antibody design

Fragment-based drug discovery

Structure-based medicinal chemistry

PhD or equivalent industry experience

Drug discovery methodologies

Scientific writing

Remote research environment

20 hours per week commitment

Education

PhD or equivalent in drug discovery/related field

Job description

This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development.

You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks.

The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions.

Responsibilities

• Design challenging, realistic drug discovery research problems based on authentic scientific workflows.
• Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated.
• Build comprehensive data rooms using real, source-grounded scientific data and documentation.
• Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source.
• Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions.
• Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility.
• Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable.
• Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly.
• Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning.
• Collaborate with project reviewers and other domain experts to refine research tasks.

Required Qualifications

• Professional expertise in one or more of the following areas:
• Mechanistic enzymology
• Structure-guided peptide design
• Structure-guided antibody design
• Fragment-based drug discovery
• Structure-based medicinal chemistry
• PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field.
• Strong understanding of drug discovery research methodologies and scientific evidence evaluation.
• Ability to construct complex scientific problems with defensible conclusions.
• Strong analytical and critical-thinking skills.
• Ability to evaluate scientific reasoning quality, not simply final answers.
• Strong scientific writing and documentation skills.
• Comfortable working independently in a remote research environment.
• Ability to commit at least 20 hours per week.

Preferred Qualifications

• Experience designing or evaluating drug discovery research strategies.
• Strong background in structure-based drug design, protein-ligand interactions, enzymology, or molecular discovery.
• Experience working with scientific literature, experimental datasets, structural data, and research documentation.
• Experience developing research assessments, scientific benchmarks, or evaluation frameworks.
• Familiarity with open-source scientific tooling and computational research workflows.
• Experience evaluating AI-generated scientific research or technical outputs is a plus.
• Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning.

Compensation

• Competitive compensation of $60-$90/hour.
• Hourly contract engagement.
• Fully remote.
• Minimum commitment: 20 hours/week.
• Up to 40 hours/week available.
• Claude Max subscription required for the project and fully reimbursed.