Drug Discovery Using AI & Machine Learning Internship
Build practical skills at the intersection of Artificial Intelligence, Machine Learning, Computational Biology, Cheminformatics and modern drug discovery. Work through structured projects involving molecular data, predictive modelling, virtual screening and AI-assisted drug research.
Why Choose This Internship?
Enter the Future of AI-Driven Drug Discovery
The Drug Discovery Using AI & Machine Learning Internship by TheNexoraGroup is designed for students, freshers and life-science learners who want to understand how artificial intelligence and computational methods are being applied to modern drug discovery.
The internship combines AI/ML fundamentals with molecular data, drug-target analysis, QSAR, molecular property prediction, virtual screening, cheminformatics and project-based learning.
You will progressively move from fundamentals to practical workflows and portfolio-oriented projects.
What You Will Experience
Build an understanding of supervised, unsupervised and deep learning approaches.
Work with molecular structures, descriptors, fingerprints and biological datasets.
Explore target identification, screening, QSAR and drug-property prediction.
Build projects that demonstrate your practical understanding.
Start Your AI Drug Discovery Journey
Applications are processed according to the currently available internship batch. Choose your internship duration and complete the registration form below.
Apply Before Today's Deadline
Enroll for Internship →
Registration Form
Fill in your details below to apply for the Drug Discovery Using AI & Machine Learning Internship.
From Fundamentals to AI Drug Discovery Projects
A structured pathway designed to take you from foundational concepts to practical computational drug discovery workflows.
AI & Biology Foundations
Understand drug discovery, biological targets, molecular data, AI concepts and the computational research ecosystem.
Python & Data Science
Work with Python, NumPy, Pandas, data cleaning, visualization and machine learning workflows.
Molecular AI
Explore molecular representations, descriptors, fingerprints, QSAR, property prediction and drug-target modelling.
Projects & Portfolio
Complete practical projects and document your work for a career-oriented portfolio.
Build Skills With Modern AI Tools
The internship introduces a practical ecosystem used for AI, molecular data analysis and computational drug discovery.
🐍 Programming & Data
🤖 AI & Machine Learning
🧬 Cheminformatics
🔬 Drug Discovery
56 Modules of AI Drug Discovery
Explore a structured curriculum covering AI, machine learning, molecular data, cheminformatics, computational drug discovery, virtual screening and project development.
Introduction to Drug Discovery
Drug discovery pipeline, stages and modern computational approaches.
Traditional vs AI-Driven Drug Discovery
Understand how AI is transforming research workflows.
Role of AI in Pharmaceutical Research
Applications of AI across modern drug research.
Drug Targets & Biological Systems
Understand targets, pathways and therapeutic relevance.
Introduction to Molecular Data
Explore chemical and biological datasets used in AI workflows.
Python for Drug Discovery
Python fundamentals for computational research.
Python Data Structures
Lists, dictionaries, functions and research-oriented data handling.
NumPy for Scientific Computing
Arrays, numerical operations and scientific calculations.
Pandas for Molecular Datasets
Data loading, cleaning and manipulation.
Data Visualization
Visualize scientific and molecular datasets.
Exploratory Data Analysis
Identify patterns, distributions and data-quality issues.
Data Cleaning & Preprocessing
Prepare datasets for reliable AI model development.
Machine Learning Fundamentals
Core concepts behind predictive machine learning.
Supervised Learning
Understand labelled-data prediction workflows.
Unsupervised Learning
Discover patterns and clusters in molecular data.
Regression for Property Prediction
Predict continuous molecular and drug-related properties.
Classification Models
Classify molecules using supervised learning approaches.
Clustering Molecular Data
Group compounds based on molecular characteristics.
Feature Engineering
Transform raw molecular data into useful model features.
Model Training & Testing
Train predictive models and evaluate their performance.
Model Evaluation Metrics
Accuracy, precision, recall, RMSE and related measures.
Overfitting & Underfitting
Understand model generalization and common modelling problems.
Cross Validation
Improve reliability of model evaluation.
Molecular Representation
Understand ways of representing chemical structures computationally.
SMILES Notation
Read and work with molecular structures in SMILES format.
Molecular Descriptors
Calculate computational descriptors from molecular structures.
Molecular Fingerprints
Generate fingerprints for molecular similarity and modelling.
RDKit Introduction
Explore cheminformatics workflows using RDKit.
Molecular Similarity
Compare compounds using computational similarity methods.
QSAR Fundamentals
Understand quantitative structure-activity relationship modelling.
QSAR Model Development
Build a practical predictive QSAR workflow.
Molecular Property Prediction
Predict drug-related molecular properties using ML.
Drug-Likeness Concepts
Understand molecular characteristics associated with drug candidates.
ADMET Fundamentals
Introduction to absorption, distribution, metabolism, excretion and toxicity.
ADMET Prediction with AI
Explore predictive modelling for drug-related ADMET properties.
Protein Structure Basics
Understand proteins, binding pockets and therapeutic targets.
Protein Data Bank
Explore publicly available protein structure information.
Protein Structure Preparation
Understand computational preparation before downstream analysis.
Drug-Target Interaction
Introduction to modelling interactions between molecules and targets.
Virtual Screening
Understand computational screening of compound libraries.
Molecular Docking Concepts
Understand docking, binding poses and scoring concepts.
Docking Workflow
Explore the computational workflow from preparation to analysis.
Deep Learning for Drug Discovery
Introduction to neural networks for molecular prediction.
Neural Networks & Molecular Data
Understand learning representations from molecular information.
AI-Based Lead Optimization
Explore how AI can assist compound prioritization and optimization.
Generative AI for Molecule Design
Introduction to AI-assisted generation of molecular candidates.
Drug Repurposing with AI
Explore computational approaches to identifying new therapeutic uses.
Network Pharmacology Concepts
Understand multi-target relationships and biological networks.
Project 1 — Molecular Property Predictor
Build an ML workflow for predicting molecular properties.
Project 2 — QSAR Activity Prediction
Create a predictive model for compound activity.
Project 3 — Molecular Similarity Engine
Build a practical similarity analysis workflow.
Project 4 — Virtual Screening Workflow
Develop a computational screening workflow for candidate prioritization.
Project 5 — Drug-Target Prediction
Develop an AI/ML workflow for interaction prediction.
Project Documentation
Document methodology, datasets, models, findings and limitations.
Portfolio Development
Convert project work into career-ready portfolio evidence.
Final Capstone Internship Project
Complete and present a structured AI drug discovery project.
Build Projects That Show What You Can Do
Move beyond theory by applying AI, ML and computational approaches to drug discovery-oriented datasets and workflows.
🧬 Major Project 01
AI-Based Virtual Screening
Develop a structured workflow for analysing molecular candidates and prioritizing compounds using computational methods.
- Molecular data preparation
- Feature generation
- Similarity analysis
- Candidate ranking
🤖 Major Project 02
Drug-Target Interaction Prediction
Develop an AI/ML-based workflow to study potential relationships between drug molecules and biological targets.
- Dataset preparation
- Feature engineering
- Model training
- Prediction evaluation
📊 Minor Project
Molecular Property Prediction
Build a machine learning model capable of predicting selected molecular or drug-related properties.
- EDA
- Descriptor generation
- Regression/classification
- Model evaluation
🔬 Practice Project
QSAR Activity Prediction
Use molecular descriptors and machine learning to explore structure-activity relationships.
🧪 Practice Project
Molecular Similarity Analysis
Use molecular fingerprints and similarity approaches to compare candidate compounds.
🚀 Capstone
AI Drug Discovery Portfolio
Combine selected workflows into a documented final project that demonstrates your learning journey.
Get Industry-Recognized Certification
Successfully complete the applicable internship requirements, assigned projects and activities to receive eligible internship completion documentation.
Build Your Experience in AI-Powered Drug Discovery
Work through practical internship activities, projects and AI-focused applications related to modern drug discovery.
Enroll for Internship →Don't Just Learn AI. Apply It.
Build interdisciplinary skills at the intersection of artificial intelligence, machine learning and life-science research.
01. AI Skills for Life Sciences
Understand how machine learning can be applied to molecular, biological and pharmaceutical datasets.
02. Portfolio-Oriented Learning
Complete practical work that can be documented and presented as evidence of your technical skills.
03. Interdisciplinary Exposure
Connect Python, machine learning, molecular science and computational drug discovery.
04. Practical Workflow
Follow a structured journey from datasets and modelling through projects and documentation.
05. Mentor Assistance
Get support during internship activities, assignments and project implementation.
06. Career Direction
Explore pathways related to computational biology, AI, bioinformatics, cheminformatics and pharmaceutical research.
Who Can Apply?
The internship can be suitable for:
Students looking to build practical AI and life-science skills.
Learners interested in computational drug discovery.
Students wanting exposure to AI applications in drug research.
Develop interdisciplinary applications of AI and ML.
Start With the Fundamentals
You do not need to be an expert in computational drug discovery to begin. The curriculum progressively introduces the concepts, tools and project workflows.
Basic familiarity with computers and an interest in AI, biology, pharmaceutical research or data science can be helpful.
Check Internship Registration →Complete Your Internship With Career Documentation
Eligible interns who successfully complete the applicable internship requirements, assigned work and project activities may receive applicable completion documentation from TheNexoraGroup.
Where Can These Skills Take You?
The skills covered can support further learning and project work across several interdisciplinary areas.
🤖 AI / ML for Life Sciences
Explore AI and machine learning applications in healthcare, biotechnology and pharmaceutical research.
🧬 Computational Biology
Build a foundation for computational analysis of biological and molecular datasets.
💊 Computational Drug Discovery
Develop exposure to AI-assisted drug screening, prediction and molecular analysis.
🔬 Bioinformatics
Extend your Python and data-analysis skills toward bioinformatics workflows.
🧪 Cheminformatics
Work with computational representations of chemical structures and molecular datasets.
📊 Research & Analytics
Strengthen your ability to analyse datasets and communicate technical project findings.
What Students Can Build
Use verified student feedback here before publishing specific names, companies or placement claims.
“The internship helped me connect machine learning concepts with pharmaceutical and molecular data. The project structure made the learning much more practical.”
Student Feedback India • AI / Life Sciences Learner“I wanted to understand how AI can be used beyond traditional software projects. The drug discovery modules gave me a useful introduction to molecular AI workflows.”
Student Feedback India • Biotechnology Learner“The combination of Python, machine learning and drug discovery made this internship especially interesting for my career goals.”
Student Feedback USA • Life Sciences / AI Learner“The project-based structure helped me understand how datasets, models and computational research workflows connect together.”
Student Feedback USA • Computational Biology Learner“I gained a better understanding of molecular descriptors, QSAR and virtual screening concepts and how machine learning can support these workflows.”
Student Feedback India • Pharmacy / Research Learner“The curriculum gives a strong starting point for anyone interested in AI-driven healthcare and computational drug discovery.”
Student Feedback USA • Biomedical Data LearnerEverything You Need to Know
Who can apply for this internship?
Students, freshers and learners from AI, computer science, biotechnology, pharmacy, life sciences, bioinformatics and related backgrounds can explore the internship.
Is this internship online?
The program is designed for online/remote participation. Specific batch arrangements can be confirmed during registration.
Do I need previous AI experience?
No advanced experience is required to start. The curriculum progressively introduces the fundamentals before moving into projects.
What will I learn?
You will explore Python, data science, machine learning, molecular representations, RDKit, QSAR, molecular property prediction, virtual screening, drug-target interaction modelling and AI-assisted drug discovery.
Will there be projects?
Yes. The curriculum includes molecular property prediction, QSAR, molecular similarity, virtual screening, drug-target prediction and a final capstone-oriented project.
Can I mention the internship on my resume?
Eligible interns can document their internship experience and project work according to the applicable completion requirements.
How long is the internship?
Available internship duration options can include 1, 2, 3, 4, 5 or 6 months. Select your preferred duration during registration or confirm it with the internship team.
Will I receive a certificate?
Eligible interns who successfully complete the applicable requirements may receive internship completion documentation.
Ready to Start Your AI Drug Discovery Journey?
Build practical knowledge across Artificial Intelligence, Machine Learning and computational drug discovery. Complete the registration form below to apply.
Applications Are Open — Apply Before Today's Deadline
Registration Form
Complete your details to apply for the Drug Discovery Using AI & Machine Learning Internship.
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FAQs
To begin, complete the registration form above by entering your name, email ID, and mobile number. Mention if you’re a student or a professional, along with your college or workplace details. You can also pick a convenient start date, and we’ll try our best to match it.
📩 Offer Letter: After we verify your registration, your offer letter will be issued and sent to your email within a few hours or the next morning.
📩 Welcome Package: On your chosen start date, you’ll receive login credentials and step-by-step guidance via email.
In case you have any queries, you can reach out through hr@corporatewebsolutions.in or WhatsApp/call +91-7618025090.
Definitely! Our support team assists with college-required documents such as attendance sheets, evaluation reports, progress updates, and project summaries throughout your program.
If you need to take a leave for any reason, simply email us or drop a WhatsApp message. You don’t have to wait for a response — just inform us and focus on your priority. Once you’re ready, you can easily resume your tasks.
Yes, a laptop or desktop with a good internet connection is mandatory for participating in this program.
Our programs feature pre-recorded video sessions and LIVE sessions both (Hybrid ) to offer maximum flexibility. Everyone — students, professionals, and mentors — can learn at their own pace without schedule conflicts.
Don’t worry there is an AI-powered assistant to help you with all your coding-related queries. Andie can check and debug code, generate new code, and even build entire projects for you.
This feature is exclusively available to registered candidates through their Task Portal.
Since mentors cannot be available 24/7, Andie was developed to bridge the gap. Located at the bottom-left corner of every module, this Full Stack Developer Bot is capable of writing, reviewing, and troubleshooting code anytime, ensuring you get instant solutions to your coding challenges, day or night.
This internship cum training opportunity is designed in such a way as from fresher to a professional anyone can get benefit out of it, The opportunity is divided into 15+ modules, and every Module contains 15-20 small tasks plus 1 project (in the last) based upon what you have learnt in that particular module. The complexity and practicality of your modules and projects will gradually increase, Timing is flexible, schedule yours accordingly. After completing every project given in the modules, Submit within the deadlines.
A major part of this program contains a training part, however we have many projects (2 Major, 15 Minor and many practice projects) and many internal and external resources to sharpen the skills of the candidates. It is a self paced program, Training and internships will go simultaneously. After every Module, there will be a project related to it (may it be a minor, major or practice project)
We have 20+ projects to provide hands on Experience and sharpen the skills of the Interns.
About Paid Projects_
Paid projects will be provided to the interns on two basis
1) The assignments/projects, which all students sends goes directly to our USA team. they evaluate all of them and create a kind of ranking sheet based upon some factors like quality, accuracy, deadline met etc. They keep this list with them for future paid projects.
2) The availability and number of the projects available.
The training is split into 15+ modules, each with 15–20 tasks and one project. As you progress, the complexity grows to ensure steady skill development. Projects must be submitted on time, and you can plan your schedule flexibly.
You’ll work on over 20 projects to build real-world experience.
👉 Paid Project Opportunity: Based on your performance (quality, speed, and accuracy), you may be eligible for paid tasks offered by our USA team, subject to availability.
Anyone interested can join! Basic knowledge of HTML, CSS, or JavaScript is a bonus but not compulsory. Graduates from any stream are welcome. There are no restrictions based on nationality, age, or background.
You decide your working hours! Whether you’re a student or a working professional, you can complete modules at your convenience. Plus, the internship is 100% remote — work from wherever you are most comfortable.
Once enrolled, you’ll have lifetime access to all training content, unless there’s a policy change in the future.
Absolutely! You’ll receive full training material, video tutorials, and 24/7 coding assistance before and during your project work.
Yes, but it depends! Stipends are offered based on your performance, the nature of the project, and USA team evaluations. Stipends typically range from ₹8,000 to ₹18,000 INR ($99 – $219) or higher, depending on project availability.
We actively hire top-performing interns for internal and client roles based on project availability. Additionally, we regularly post openings from our partners so you can apply even after completing the program.
Your certificate will be automatically prepared and scheduled to be emailed around your program completion date. Allow up to 48 extra hours if it falls on a weekend or holiday.
LORs are awarded to exceptional candidates based on strict performance criteria. If you require a LOR for special circumstances like studying abroad, you may also directly request it from HR.
Of course! Although not mandatory, if you find the program valuable, feel free to refer it to friends, classmates, or colleagues who might benefit.
Duration: Choose Your Internship Length —
1, 2, 3, 4, 5, or 6 Months (Online & Remote)
Stipend Given – Check Internship Overview
REGISTRATION FORM
Fill up the Below form to get registered in the program
🔬 Drug Discovery using AI & Machine Learning Internship Learning, you will gain:
Machine Learning model development
Python for AI applications
Data preprocessing and analysis
Real-world AI project experience
Industry-ready technical skills
Explore more internship opportunities at The Nexora Grop
