Internship Project-Based Live All Levels Dr. Omics Edu

6 Month CADD Research Internship with Publication Support Online

The 6-Month CADD Research Internship with Publication Support Online— A Research-Oriented for Industry-Ready Design Professionals is a project-centric programme designed to bridge the gap between academic knowledge and industry-oriented drug discovery research.

  • 5.0/5
  • English
  • Updated Oct 2026
INR

₹50000

₹60000 17% off
USD

$630

$700 10% off

Indian learners pay in INR; international learners are billed in USD.

Enroll for International Students

Paying from outside India? Use this link to complete your payment.

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6 Month CADD Research Internship with Publication Support Online

About this internship

The 6 Month CADD Research Internship with Publication Support Online at Dr. Omics Edu is a 6-month live, mentor-supervised internship in computer-aided drug design (CADD) under NEP 2020. It is a research-grade programme that follows one CADD question across six months towards publication. You work on a real dataset and a defined research question, and you finish with a docking or virtual screening project on a real drug target that you can show to an admissions panel, a guide or an employer.
In this internship you move through target identification and structure preparation, virtual screening and molecular docking and pharmacophore modelling and qsar concepts, then apply them in your own project. The programme runs live online with 7 modules, so you can ask your mentor questions as you work. It is open to learners at every level, and mentors adjust the pace to your background.

What you will achieve

Target identification and structure preparation
Virtual screening and molecular docking
Pharmacophore modelling and QSAR concepts
ADMET and toxicity prediction
Molecular dynamics simulation and trajectory analysis
Research paper writing and publication support
For careers: Computational chemist, CADD scientist, drug discovery research associate, cheminformatics analyst, and a stronger profile for pharma R&D roles or higher studies.

The project work

Hands-on implementation of everything covered in the sessions
Industry-standard tools and workflows
Project documentation and a final presentation
Code review and optimisation sessions with your mentor

Skills you will gain

PDB PubChem AutoDock Vina PyMOL Discovery Studio Visualizer SwissADME GROMACS
Certification

Available

Issued by Dr. Omics Edu

Internship curriculum

7 modules

  • Introduction to the CADD Interface and AI-enhanced workspace setup.
  • Mastering Coordinate Systems, Layers, and Standardized Documentation.
  • Development of complex 3D Part Assemblies and Kinematic Simulations.
  • Utilization of Generative Design algorithms to optimize material usage.
  • Creation of photorealistic Architectural & Mechanical Renderings.
  • Final Capstone Project: Designing a market-ready industrial component or structural layout.

  • Topic 1 = Introduction to Bioinformatics
  • Topic 2 = NCBI Database Overview
  • Topic 3 M1T3 = Genbank Database Practical Exercises
  • Topic 4 M1T4 = UCSC Genome Browser Overview
  • Topic 5 M1T5 = UCSC Genome Browser Hands-on Exercises
  • Topic 6 M1T6 = Pubmed Database Introduction
  • Topic 7 M1T7 = Clinvar Database Overview
  • Topic 8 M1T8 = KEGG Database Overview and Exercises
  • Topic 9 M1T9 = Protein Databases (UniProt)
  • Topic 10 M1T10 = Protein Databases (PDB)
  • Topic 11 M1T11 = Online BLAST Introduction and Exercises
  • Topic 12 M1T12 = Standalone BLAST Setup and Exercises
  • Topic 13 M1T13 = Standalone BLAST Advanced Exercises
  • Topic 14 M1T14 = Multiple Sequence Alignment with ClustalW
  • Topic 15 M1T15 = Multiple Sequence Alignment with MEGAA

  • Topic 1 M2T1 = Overview and Installation of Linux
  • Topic 2 M2T2 = Basic Linux Commands
  • Topic 3 M2T3 = Advanced Linux Commands
  • Topic 4 M2T4 = Package Management using Repository
  • Topic 5 M2T5 = Package Management using Source Code

  • Topic 2 M3T1 = Introduction to Python
  • Topic 3 M3T2= Data Types
  • Topic 4 M3T3= String Handling
  • Topic 5 M3T4= Data Structure
  • Topic 6 M3T5=Control Structure
  • Topic 7 M3T6 = Function
  • Topic 8 M3T7= File Handling
  • Topic 9 M3T8= Data Manipulation
  • Topic 10 M3T9= Data Visualization
  • Topic 11 M3T10= Biopython

  • Topic 1 M4T1 = Introduction and Installation of R
  • Topic 2 M4T2= Data Types in R
  • Topic 3 M4T3= Data Structure
  • Topic 4 M4T4= File Handling
  • Topic 5 M4T5=Control Structure
  • Topic 6 M4T6 = Function
  • Topic 7 M4T7= Package Management
  • Topic 8 M4T8= Data Manipulation
  • Topic 9 M4T9= Data Visualization
  • Topic 10 M4T10= Statistical Analysis

  • Topic 1 M6T1 =Introduction to Drug Discovery Process
  • Topic 2 M6T2=Role of Computational Methods
  • Topic 3 M6T3= Hands-on: Chemical Structure Visualization
  • Topic 4 M6T4= Biomolecules and Their Properties
  • Topic 5 M6T5= Structure of Proteins and Ligands
  • Topic 6 M6T6= Hands-on: Protein Structure Visualization
  • Topic 7 M7T7= Molecular Visualization Tools
  • Topic 8 M6T8= Molecular Mechanics and Dynamics Simulations
  • Topic 9 M6T9= Molecular Mechanics and Dynamics Simulations (continued)
  • Topic 10 M6T10= Chemical Databases and Data Mining
  • Topic 11 M6T11= Ligand and Structure-Based Virtual Screening
  • Topic 12 M6T12= Hands-on: Chemical Data Exploration
  • Topic 13 M6T13= Advanced Virtual Screening Techniques
  • Topic 14 M6T14= Virtual Screening using Autodock Vina
  • Topic 15 M6T15= Principles of Molecular Docking
  • Topic 16 M6T16= Scoring Functions in Docking
  • Topic 17 M6T17= Hands-on: Molecular Docking
  • Topic 18 M6T18= Introduction to Molecular Dynamics
  • Topic 19 M6T19= Simulation Software (e.g., GROMACS)
  • Topic 20 M6T20= Hands-on: Analyzing MD Data
  • Topic 21 M6T21= Chemoinformatics: Data Analysis and Visualization
  • Topic 22 M6T22= Protein-Ligand Interaction Analysis
  • Topic 23 M6T23= Hands-on Protein-Ligand Interaction Analysis
  • Topic 24 M6T24= Pharmacophore Modeling and Applications
  • Topic 25 M6T25= Chemoinformatics: Data Analysis and Visualization (continued)
  • Topic 26 M6T26= Structure-Based Drug Design
  • Topic 27 M6T27= Ligand-Based Drug Design
  • Topic 28 M6T28= Hands-on Structure-Based and Ligand-Based Drug Design
  • Topic 29 M6T29= ADMET in Drug Development
  • Topic 30 M6T30= Course Conclusion

  • Topic 1 M7T1= Basics of Machine Learning
  • Topic 2 M7T2= Supervised, Unsupervised, and Reinforcement Learning
  • Topic 3 M7T3= Hands-on: Learn the Basics with scikit-learn Library in Python
  • Topic 4 M7T4= Data Cleaning and Feature Selection
  • Topic 5 M7T5= Handling Molecular Data
  • Topic 6 M7T6= Hands-on: Use Pandas and NumPy for Data Preprocessing
  • Topic 7 M7T7= Regression and Classification Algorithms
  • Topic 8 M7T8= Deep Learning in Drug Discovery
  • Topic 9 M7T9= Hands-on: Implement Machine Learning Models using scikit-learn
  • Topic 10 M7T10= Hands-on: Implement Machine Learning Models using TensorFlow/Keras
  • Topic 11 M7T11= Predicting Drug-Target Interactions
  • Topic 12 M7T12= QSAR Modeling
  • Topic 13 M7T13= Hands-on: Apply Machine Learning to Real Datasets with RDKit
  • Topic 14 M7T14= Hands-on: Apply Machine Learning to Real Datasets with Cheminformatics
  • Topic 15 M7T15= Structure-Activity Relationship (SAR) Analysis
  • Topic 16 M7T16= Hands-on: Use RDKit for SAR Analysis
  • Topic 17 M7T17= De Novo Drug Design using ML
  • Topic 18 M7T18= Explore De Novo Design Tools
  • Topic 19 M7T19= Advanced Machine Learning Techniques in Drug Design
  • Topic 20 M7T20= Integration of Omics Data in Drug Discovery
  • Topic 21 M7T21= Clinical Trial Design and Data Analysis
  • Topic 22 M7T22= Ethical Considerations in Drug Design and Machine Learning
  • Topic 23 M7T23= Real-World Applications
  • Topic 24 M7T24= Q&A and discussion
  • Topic 25 M7T25= Conclusion

What you need to start

  • Basic knowledge of Biology, Biochemistry, Biotechnology, Pharmacy, Bioinformatics, or a related field
  • Fundamental understanding of molecular biology and biomolecules
  • Basic computer and internet skills
  • No advanced programming experience is mandatory; programming concepts will be introduced as required
  • Suitable for learners interested in computational drug discovery and pharmaceutical research

Who this internship is for

  • B.Pharm, M.Pharm, B.Sc, M.Sc, B.Tech, M.Tech and PhD students in pharmacy, chemistry, biotechnology, biochemistry or life sciences.
INR

₹50000

₹60000 17% off
USD

$630

$700 10% off

Indian learners pay in INR; international learners are billed in USD.

Enroll for International Students

Paying from outside India? Use this link to complete your payment.

Make an Enquiry
Active batch
Open for enrolment
01092026 - 6-Month CADD Research Internship with Publication Support Online
  • Starts 15 Sep 2026
  • Ends 28 Feb 2027
  • Timing 7:00 PM – 8:00 PM
  • Days Mon, Tue, Wed, Thu, Fri
  • Platform MS Teams
This internship includes
  • Format Live
  • Level All Levels
  • Language English
  • Modules 7
  • Live project Yes
  • Certificate Yes
  • Provider Dr. Omics Edu
  • 6-Month Research-Oriented CADD Programme
  • Live
  • interactive
  • mentor-guided training
  • Hands-on computational drug discovery workflows
  • Real-world datasets and research case studies
  • Project-based learning from target identification to computational validation
  • Practical exposure to molecular docking
  • virtual screening
  • pharmacophore modeling
  • QSAR
  • and molecular dynamics
  • AI/ML applications in modern drug discovery
  • Research methodology and scientific literature analysis
  • Guidance on data interpretation
  • visualization
  • and scientific reporting
  • Research-oriented CADD projects
  • Project documentation and presentation guidance
  • Industry-oriented computational workflows and best practices
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