Research, innovation, and data-driven problem solving are the future of science and technology. At IRC, we believe students should not just learn concepts but also apply them in real-life projects. That’s why our internship program is designed to bridge the gap between academics and industry research. With IRC internships, you’ll gain hands-on experience, mentorship from experts, and opportunities to publish and present your work.
Admission is Open Now
IRC’s internship introduces students to real-world projects in life science, bioinformatics, computational biology, data science, and applied technology. Along with technical training, students gain research skills, scientific writing practice, and teamwork experience.
You’ll learn not just the fundamentals but also how to apply them in professional projects. By the end of the program, interns will have:
Overview of Bioinformatics What is Computer-Aided Drug Design (CADD)? Importance of computational tools in modern drug discovery Real-life applications in pharmaceutical research
What is scientific research? Types of research (basic vs applied, qualitative vs quantitative) Hypothesis formulation, experimental design Literature review techniques
Structure and function of DNA, RNA, and proteins Central dogma of molecular biology Introduction to enzymes and receptors Protein folding and its importance in drug discovery
Introduction to PDB, UniProt, PubChem, ChEMBL How to retrieve and prepare biomolecules Ligand and receptor preparation for docking Tools: PyMOL, Chimera, AutoDock Tools
Overview of Bioinformatics What is Computer-Aided Drug Design (CADD)? Importance of computational tools in modern drug discovery Real-life applications in pharmaceutical research
ADME properties (Absorption, Distribution, Metabolism, Excretion) Drug-likeness rules (Lipinski’s Rule of 5) Predicting toxicity and side effects Tools: SwissADME, pkCSM, ProTox
What is MDS and why is it important? Force fields and simulation parameters Solvation, energy minimization, and equilibration Tools: GROMACS, CHARMM
Root Mean Square Deviation (RMSD) Root Mean Square Fluctuation (RMSF) Radius of Gyration (Rg), H-bonds Visualizing trajectories using VMD or PyMOL
Basics of quantum mechanics in chemistry HOMO-LUMO, molecular orbitals, dipole moment Tools: Gaussian, ORCA, Avogadro
Choosing a suitable research topic Project planning and timeline management Writing objectives, methodology, expected outcomes Collaboration and publication ethics
Importance of referencing in research How to cite sources properly (APA, MLA, etc.) Tools: Mendeley, Zotero, EndNote Organizing and sharing reference libraries
What is Python and why use it in research? Basic syntax, variables, data types Conditional statements, loops, functions Running scripts in Jupyter Notebook
Introduction to NumPy and Pandas Data visualization with Matplotlib and Seaborn Bioinformatics libraries (Biopython, RDKit basics) Data cleaning and analysis techniques
What is a graphical abstract? Importance in scientific communication Tools: BioRender, Canva, Adobe Illustrator basics Tips for designing effective visuals
How to write a professional academic CV Writing an impactful Statement of Purpose (SOP) Requesting and structuring Letters of Recommendation (LOR) Common mistakes to avoid and expert tips
Note for Students:
Each module is designed to help you gain hands-on experience and theoretical knowledge essential for careers in computational biology, bioinformatics, and drug discovery research. By the end of the internship, you’ll be equipped to start your own research project or contribute to ongoing studies.
● Python (Pandas, NumPy, Scikit-learn, Matplotlib)
● R Programming
● PyMOL & AutoDock (for CADD projects)
● Excel, SPSS (for Biostatistics)
● Google Colab & Kaggle
● Research Databases (NCBI, PDB, PubMed)
● University Students (Pharmacy, Biotech, MBBS, BDS, Microbiology, Genetics,
Biochemistry, Food & Nutrition, Environmental Science, Agriculture, Botany,
Marine Science )
● Job Seekers looking for research careers
● Freelancers aiming for scientific data projects
● Homemakers & Enthusiasts interested in research
● Anyone willing to explore Research & Innovation
After completing IRC Internship, you can pursue careers such as:
● Research Assistant
● Data Analyst (Life Science)
● Bioinformatics Specialist
● Public Health Analyst
● CADD Researcher
● Academic & Industry Research Positions
Enroll from anywhere and join our live research-based sessions.
Dedicated review sessions to clarify concepts and help in skill development.
Once you’re part of IRC, you’re always connected. We provide career and research support beyond the internship.
We guide interns in preparing abstracts, research papers, and publishing in reputed journals.
Our team helps you with resume building, networking, and connecting with research labs & companies.
We treat every intern as part of the IRC family. Your feedback helps us grow and improve our programs.
1 review for Internship 2
Reyad Sheikh –
this is perfect