Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD) - Remote

Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD) - Remote

Job Type: Contract
Work Location: Remote – Worldwide
Openings: 50
Compensation: $93,600–$187,200 annually ($45–$90/hour)
Experience Level: PhD / Advanced Research
Field: Computational Chemistry, Structural Biology, Bioinformatics & Drug Discovery

About the Role

Are you a PhD-level scientist with expertise in computational chemistry, structural biology, or drug discovery?

Join an expert scientific research team contributing to the development and evaluation of next-generation artificial intelligence (AI) systems. In this remote contract role, you will leverage your scientific knowledge, research experience, and analytical skills to improve how advanced AI models understand, reason about, and solve complex scientific problems.

You will develop challenging, research-driven scientific problems, evaluate AI-generated responses, validate scientific reasoning, and create high-quality reference solutions grounded in established methodologies and peer-reviewed literature.

This opportunity is particularly suited to researchers with strong academic or industry backgrounds who can critically assess complex scientific work and communicate advanced concepts with precision.

Key Responsibilities

• Design and develop challenging, expert-level scientific problems covering computational chemistry, structural biology, biophysics, and drug discovery.

• Create accurate, reproducible, and verifiable reference solutions to complex scientific questions.

• Evaluate AI-generated scientific outputs for accuracy, methodological rigor, logical consistency, and depth of reasoning.

• Identify subtle scientific errors, unsupported conclusions, flawed assumptions, and limitations in AI-generated research.

• Develop detailed evaluation rubrics, benchmarks, and reference answers based on primary literature and established scientific methodologies.

• Apply expertise in molecular modeling, molecular dynamics simulations, protein structure prediction, protein design, molecular docking, virtual screening, and computational drug discovery.

• Assess scientific approaches involving QSAR/QSPR, ADMET prediction, cheminformatics, proteomics, and metabolomics.

• Document scientific reasoning and provide clear explanations that allow other specialists to independently assess and validate findings.

• Incorporate feedback and participate in iterative quality assurance and peer-review processes.

Required Qualifications

Applicants must meet the following requirements:

• PhD in Computational Chemistry, Structural Biology, Biophysics, Bioinformatics, Medicinal Chemistry, Biochemistry, or a closely related scientific discipline.

• Hands-on research experience in an academic, pharmaceutical, biotechnology, or industry laboratory. Wet-lab experience is an advantage.

• Strong understanding of scientific research methodologies, experimental validation, and computational analysis.

• Demonstrated expertise in at least one or more relevant areas of computational chemistry, structural biology, or drug discovery.

• Excellent scientific writing, analytical reasoning, and technical documentation skills.

• Professional proficiency in written and spoken English (C1 level or higher).

• Ability to communicate complex scientific concepts accurately and clearly.

Preferred Technical Expertise

Experience in the following areas will be highly advantageous:

1. Molecular Modeling & Simulation

• Molecular dynamics simulations using GROMACS, AMBER, NAMD, or OpenMM.

• Free energy calculations and methods, including FEP and thermodynamic integration (TI).

• Molecular interactions, binding affinity estimation, and computational biophysics.

2. Structural Biology & Protein Modeling

• Protein structure prediction, modeling, and design using AlphaFold, Rosetta, and homology modeling.

• Interpretation of cryo-EM and X-ray crystallography data.

• Protein–ligand interactions and structural analysis.

3. Molecular Docking & Virtual Screening

• Molecular docking and virtual screening workflows.

• Experience with AutoDock, Glide, Schrödinger Suite, or MOE.

• Structure-based drug design and computational hit identification.

4. Cheminformatics & Computational Drug Discovery

• RDKit and molecular descriptor analysis.

• QSAR/QSPR modeling and molecular property prediction.

• ADMET prediction, molecular fingerprinting, and chemical library design.

• Machine learning applications in molecular discovery.

5. Proteomics & Metabolomics

• LC-MS/MS-based proteomics and metabolomics workflows.

• MaxQuant and DIA/DDA data analysis.

• Post-translational modification (PTM) analysis.

• Untargeted metabolomics and biological data interpretation.

6. Programming & Machine Learning

• Python programming and scientific computing.

• R, Bash, or similar programming and scripting tools.

• Machine learning for molecular property prediction.

• Experience with graph neural networks (GNNs), generative models, or AI-assisted molecular discovery is an advantage.

Additional Advantages

• Postdoctoral research or industry experience in pharmaceutical, biotechnology, or drug discovery environments.

• Strong peer-reviewed publication record, particularly first-author publications in relevant scientific journals.

• Experience with scientific benchmarking, AI model evaluation, or technical research review.

• Previous involvement in interdisciplinary research or computational drug discovery projects.

• Ability to independently assess scientific evidence and distinguish reliable conclusions from unsupported interpretations.

What This Opportunity Offers

• Fully Remote: Work from anywhere in the world.

• Competitive Compensation: Earn $45–$90 per hour, equivalent to $93,600–$187,200 annually at 40 hours per week.

• Flexible Contract Engagement: Apply your specialist knowledge through remote research-focused assignments.

• Scientific Impact: Contribute to improving the scientific reasoning and capabilities of next-generation AI systems.

• Advanced Research Exposure: Work on complex problems spanning computational chemistry, structural biology, molecular sciences, and drug discovery.

Who Should Apply?

This opportunity is ideal for PhD-qualified scientists, computational chemists, structural biologists, bioinformaticians, biophysicists, medicinal chemists, and drug discovery researchers with strong analytical and scientific communication capabilities.

Researchers with experience translating complex scientific knowledge into structured problems, validated solutions, and rigorous technical evaluations are particularly encouraged to apply.

Apply Now

If you have advanced scientific expertise and want to contribute to the development of next-generation AI technologies, submit your application for consideration.