Research Scientist

Job Summary

Join Keystone Recruitment's customer’s team as a Biochemist & Biophysicist AI Trainer, where your expertise in molecular and structural biology will directly shape the development of advanced AI models. This Research Scientist role focuses on bridging cutting-edge life sciences with artificial intelligence, ensuring scientific datasets and AI outputs are accurate, relevant, and actionable for research and industrial applications.

Key Responsibilities

• Collaborate with interdisciplinary teams to design AI training workflows focused on biochemistry, biophysics, and molecular biology.
• Curate, annotate, and validate large-scale scientific datasets to enhance AI learning and model accuracy.
• Evaluate AI model performance, providing critical feedback and domain-specific insights for continuous improvement.
• Develop problem sets, scenarios, and use cases to effectively train and test AI systems in life sciences.
• Document training methodologies and communicate findings to both technical and non-technical stakeholders.
• Stay updated on computational methods, AI advancements, and emerging trends in biochemistry and biophysics.
• Mentor internal contributors and facilitate knowledge transfer on best practices for scientific AI model training.

Required Skills and Qualifications

• Advanced degree (Master’s or PhD) in Biochemistry, Biophysics, or a closely related field.
• Proven expertise in molecular biology, structural biology, or physical biochemistry.
• Experience in data curation, annotation, and analysis within scientific research contexts.
• Strong written and verbal communication skills with the ability to report scientific findings clearly.
• Proficiency with computational tools and familiarity with AI or machine learning concepts.
• Ability to work autonomously in a fully remote environment.
• Collaborative mindset with meticulous attention to detail.

Preferred Qualifications

• Hands-on experience with AI training, large language models (LLMs), or natural language processing in life sciences.
• Background in interdisciplinary project management or scientific communication.
• Prior experience mentoring or teaching in academic or industry settings.

Key skills/competency

• Biochemistry
• Biophysics
• Molecular Biology
• AI Training
• Data Curation
• AI Model Evaluation
• Computational Tools
• Life Sciences
• Scientific Communication
• Interdisciplinary Collaboration