AI-Driven Drug Discovery Research Intern
PSPM Technologies Pvt Ltd
IndiaFresher38m agovia LinkedIn
About the Role
This is a remote, unpaid 6-month research and learning initiative for an AI-Driven Drug Discovery Research Intern.
Key Responsibilities
- Support research initiatives focused on AI-driven drug discovery.
- Design and execute in silico experiments.
- Analyze pharmacological and biochemical datasets.
- Assist in building proof-of-concept models for pharmaceutical applications.
- Conduct literature reviews.
- Perform data collection and preprocessing.
- Collaborate with AI/ML engineers on model development.
- Document methods, results, and insights for internal reports and presentations.
- Contribute to hypothesis generation and target identification.
- Evaluate potential drug candidates using computational tools and AI-based approaches.
- Work closely with cross-functional teams in technology and pharma innovation.
Requirements & Tech Stack
- Backgrounds such as M.Pharm Pharmacology + M.Sc Biotechnology or M.Pharm Pharmaceutical Chemistry + M.Sc Bioinformatics, or equivalent postgraduate qualifications in related fields.
- Skills in pharmacology and pharmaceutical sciences, including understanding of drug mechanisms of action, ADME/PK concepts, and basic toxicology and therapeutic areas relevant to drug discovery.
- Skills in biotechnology and bioinformatics, such as molecular biology fundamentals, sequence analysis, structural biology concepts, and familiarity with biological databases and tools.
- Computational and analytical skills, including data analysis, statistical interpretation, and the ability to work with large scientific datasets.
- Experience with any programming or scripting language (e.g., Python, R) is beneficial.
- Understanding of AI/ML applications in life sciences, with interest or exposure to machine learning concepts, predictive modeling, or in silico drug design.
- Prior coursework or projects in AI-driven drug discovery are an advantage.
- Research-oriented skills such as literature review, experimental design, and scientific writing.