Remote Computational Biology & Medicinal Chemistry for AI

SaidGig; New York (NY); A distancia; USD 124.000 - 165.000; Jornada completa

Descripción de la vacante

SaidGig is seeking a researcher to apply computational biology and medicinal chemistry to train AI systems. The role focuses on analyzing complex biological datasets and providing domain-specific feedback to improve AI outputs in medicinal chemistry contexts.

You will develop problem sets and collaborate with experts to validate findings, while refining data-curation best practices for computational biology work.

Formación

• Advanced degree (PhD/PharmD/MSc) in computational biology, medicinal chemistry, bioinformatics or related field.
• Medicinal chemistry expertise with drug discovery or design experience.
• Strong analytical skills with biological datasets and literature.
• Experience applying computational methods to chemistry/biology problems.

Responsabilidades

• Analyze and annotate complex biological datasets for medicinal chemistry.
• Provide domain-specific feedback to improve AI systems in computational biology.
• Evaluate scientific content for accuracy, relevance, and clarity.
• Develop and review problem sets and scenarios based on real-world medicinal chemistry challenges.
• Collaborate asynchronously with experts to validate findings and share perspectives on deliverables.
• Refine data-curation methodologies and best practices for computational biology work.

Conocimientos

Analytical skills

Communicate science clearly

Cross-disciplinary collaboration

Experience with AI-driven projects

Data interpretation

Educación

PhD

MSc

PharmD

Herramientas

Bioinformatics tools

Cheminformatics platforms

Data-analysis software

Descripción del empleo

SaidGig is seeking a researcher to apply computational biology and medicinal chemistry to train AI systems. The role focuses on analyzing complex biological datasets and providing domain-specific feedback to improve AI outputs in medicinal chemistry contexts.

You will develop problem sets and collaborate with experts to validate findings, while refining data-curation best practices for computational biology work.