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School of Health Sciences & Technology
Program details
The B.Tech in Bioinformatics is an interdisciplinary program that blends biology, computer science, mathematics and data analytics to prepare students for emerging roles in life sciences and health technology. Students build a strong foundation in molecular biology, genomics, biochemistry and microbiology, alongside practical capability in programming, databases, algorithms, artificial intelligence and machine learning. A strong research focus enables students to explore areas such as precision medicine, computational drug discovery, cancer genomics and AI-driven biology through guided projects and thesis work.
Program Highlights
- Interdisciplinary training across biology, computer science, mathematics, statistics and data analytics.
- Hands-on programming in C, Java and Python/R, supported by data structures, algorithms, databases, cloud computing and Linux.
- Integrated wet-lab and computational exposure in genomics, microbiology and analytical techniques.
- Training in contemporary bioinformatics workflows including NGS analysis, transcriptomics, proteomics and molecular modelling.
- Applications of AI and machine learning in disease prediction and drug discovery.
- Industry-aligned projects and capstone work across bioinformatics, healthcare informatics and biotech R&D.
Industry Trends & Career Opportunities
Bioinformatics is now central to modern life sciences, driven by rapid advances in genomics and multi-omics, biotechnology, and data-led healthcare. The rise of personalised medicine and genetic screening, AI-enabled drug discovery, and the explosion of biological data from sequencing and digital health platforms are reshaping diagnosis, treatment and biomedical research worldwide. Demand is growing for professionals who can interpret complex biological data and build computational solutions for real biomedical challenges.
Typical roles include:
- Bioinformatics analyst / scientist
- Computational biologist
- NGS data analyst (clinical or research)
- Clinical bioinformatician
- Machine learning specialist (life sciences)
- Cheminformatics and drug discovery specialist
- Genomics / proteomics lab analyst
- Research scientist (biotech, pharma or academia)
- Product and IT-bio roles; entrepreneurship in bioinformatics tools and diagnostics
Placements
The program offers strong placement prospects, supported by a curriculum that integrates biological sciences with advanced computational and analytical training. Graduates are well-prepared for roles in genomics diagnostics, computational drug discovery, healthcare informatics, multi-omics research and biomedical innovation. Many students also progress to higher studies in India and abroad, or move into research and doctoral pathways, reflecting sustained global demand for bioinformatics talent in precision medicine and life-science innovation.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Engineering & Economic Foundations
The first year focuses on the "Common Engineering Core" required by AICTE, with early introduction to Economic Principles.
Semester 1
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Engineering Mathematics - I (Linear Algebra & Calculus) | 3 | 1 | 0 | 4 |
| Engineering Physics (with Lab) | 3 | 0 | 2 | 4 |
| Programming for Problem Solving (C/Python) | 3 | 0 | 4 | 5 |
| Principles of Microeconomics | 3 | 0 | 0 | 3 |
| Professional Communication Skills | 2 | 0 | 2 | 3 |
| TOTAL | 19 |
Semester 2
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Engineering Mathematics - II (ODE & Multivariable Calculus) | 3 | 1 | 0 | 4 |
| Engineering Chemistry (with Lab) | 3 | 0 | 2 | 4 |
| Data Structures & Algorithms (with Lab) | 3 | 0 | 4 | 5 |
| Principles of Macroeconomics | 3 | 0 | 0 | 3 |
| Workshop & Manufacturing Practices | 1 | 0 | 4 | 3 |
| TOTAL | 19 |
Year 2: Core Interdisciplinary Integration
The transition from general engineering to specialized computational economics begins here.
Semester 3
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Discrete Mathematical Structures | 3 | 1 | 0 | 4 |
| Object-Oriented Programming (Java/C++) | 3 | 0 | 2 | 4 |
| Intermediate Microeconomics (Mathematical) | 3 | 1 | 0 | 4 |
| Econometrics - I (Statistical Inference) | 3 | 0 | 2 | 4 |
| Digital Logic & Computer Organization | 3 | 0 | 0 | 3 |
| TOTAL | 19 |
Semester 4
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Design and Analysis of Algorithms | 3 | 0 | 2 | 4 |
| Operating Systems (with Lab) | 3 | 0 | 2 | 4 |
| Econometrics - II (Time Series & Forecasting) | 3 | 0 | 2 | 4 |
| Intermediate Macroeconomics | 3 | 1 | 0 | 4 |
| Database Management Systems | 3 | 0 | 2 | 4 |
| TOTAL | 20 |
Year 3: Specialized Computational Economics
Focus shifts to "Mechanism Design" and "FinTech," where code meets market theory.
Semester 5
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Game Theory & Strategic Behavior | 3 | 1 | 0 | 4 |
| Artificial Intelligence & Machine Learning | 3 | 0 | 2 | 4 |
| Computational Finance & Algorithmic Trading | 2 | 0 | 4 | 4 |
| Computer Networks | 3 | 0 | 0 | 3 |
| Professional Elective - I (See Baskets) | 3 | 0 | 0 | 3 |
| Mini Project (Market Simulation) | 0 | 0 | 4 | 2 |
| TOTAL | 20 |
Semester 6
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Mechanism Design & Auction Theory | 3 | 1 | 0 | 4 |
| Econometrics with Machine Learning | 3 | 0 | 2 | 4 |
| Professional Elective - II | 3 | 0 | 0 | 3 |
| Open Elective - I (Management/Law) | 3 | 0 | 0 | 3 |
| Environmental Sciences (Mandatory Audit) | 2 | 0 | 0 | NC |
| Summer Internship (Industry/Research) | – | – | – | 3 |
| TOTAL | 17 |
Year 4: Synthesis & Industry Readiness
Final year is dedicated to high-level electives and a significant Capstone project.
Semester 7
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Behavioral Economics & Digital Platforms | 3 | 0 | 0 | 3 |
| Professional Elective - III | 3 | 0 | 0 | 3 |
| Professional Elective - IV | 3 | 0 | 0 | 3 |
| Open Elective - II | 3 | 0 | 0 | 3 |
| Capstone Project Phase - I | 0 | 0 | 12 | 6 |
| TOTAL | 18 |
Semester 8
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Full Semester Industry Internship / Major Project | 0 | 0 | 24 | 12 |
| TOTAL | 12 |
Eligibility
Interested students must meet the following minimum eligibility criteria for B.Tech. Bioinformatics:
- Minimum 50% Marks at X & XII with Physics, Chemistry, Biology/ Math’s
- English as a Major Subject in XII
Selection Criteria
Admission into the B.Tech. Bioinformatics program at UPES relies on:
- Individual's performance in UPESEAT / JEE Mains / Board Merit / SAT / CUET as the selection criteria for students interested in pursuing the course.
