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Eli Lilly Hiring Genomics & AI Interns | Bioinformatics & AI Roles (Freshers)
Eli Lilly
Bangalore
Freshers
AI + Genomics
Internship
🏢 About Company
Eli Lilly is a global pharmaceutical leader integrating Artificial Intelligence with genomics and drug discovery. It offers cutting-edge exposure to real-world pharma innovation and data science.
1️⃣ Genomics – AI Engineer Intern
📌 Responsibilities:- Work on multi-omics datasets (GWAS, RNA-seq, eQTL)
- Build ML/DL models for sequence analysis
- Variant prediction & genomic modeling
- Develop scalable pipelines for genomic data
- Python + ML/DL (PyTorch / TensorFlow)
- Genomics fundamentals (DNA, RNA, gene expression)
- Data processing & pipelines
2️⃣ Small Molecule – AI Engineer Intern
📌 Responsibilities:- Build AI models for drug discovery
- Work on datasets (ChEMBL, PubChem, DrugBank)
- Generative AI for molecule design
- ADMET & SAR modeling
- Python + RDKit
- Drug discovery concepts (SAR, ADMET)
- ML models & cheminformatics
🎓 Eligibility
- Bachelor’s / Master’s in Bioinformatics / AI / CS / Computational Biology
- Strong programming + ML fundamentals
💰 Stipend
- ₹40,000 – ₹90,000/month
🎯 Interview Tips (Must Read)
For Genomics Role:- Revise DNA, RNA, gene expression basics
- Understand sequencing & variant analysis
- Prepare ML projects on biological data
- Learn ADMET, SAR basics
- Understand molecule representation (SMILES)
- Practice RDKit-based projects
- Strong Python coding practice
- Explain ML projects clearly
- Revise deep learning basics
📚 Resources:
📌 Note Before You Apply:
Choose the role based on your core skillset. AI + Pharma roles are highly competitive — apply early.
Choose the role based on your core skillset. AI + Pharma roles are highly competitive — apply early.
🚀 Select Role & Apply Directly
🤖 Advanced Intelligence & Computational Research Insights:
Eli Lilly's AI research divisions focus on deploying cutting-edge machine learning architectures for therapeutic innovations. Before submitting your profile on their Workday network, ensure your CV showcases solid conceptual knowledge of computational genomics, molecular structure analysis, data modeling frameworks (Python/R), and algorithmic approaches to digital healthcare pipelines.
Eli Lilly's AI research divisions focus on deploying cutting-edge machine learning architectures for therapeutic innovations. Before submitting your profile on their Workday network, ensure your CV showcases solid conceptual knowledge of computational genomics, molecular structure analysis, data modeling frameworks (Python/R), and algorithmic approaches to digital healthcare pipelines.
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