Industry-aligned curriculum
Months of industry internship experience
Core Pillars: AI & ML, Genetics, Computational Biology, Omics Technologies
The programme is designed to prepare students for the emerging convergence of biology and artificial intelligence, enabling them to apply computational intelligence to genetics and genomics for real-world impact.
The programme integrates genetics, genomics, bioinformatics, and artificial intelligence to enable a deeper, data-driven understanding of complex biological systems.
Emphasises the use of large-scale genomic data and artificial intelligence algorithms to identify patterns, predict disease risk, and support advancements in precision medicine.
Encourages the development of AI-enabled solutions that translate genomic insights into practical applications across healthcare, biotechnology, and agriculture.
Trains students to apply machine learning, data science, and computational tools to analyse and interpret complex biological data.
Promotes the responsible use of genetic data while addressing issues of privacy, bioethics, and broader societal implications in the era of AI-driven biology.
The most distinctive feature of the programme is the integration of advanced genomics with artificial intelligence, enabling students to analyse large-scale genetic data and develop predictive biological models. Through hands-on training in bioinformatics, machine learning, and genomic analytics, the programme prepares students to address real-world challenges in precision medicine, disease prediction, and biotechnology innovation.
| Year | Core Learning Domain | Description |
|---|---|---|
| Year 1 | Foundations | Exposure to core concepts in genetics, biology, mathematics, and programming, along with basic wet-lab skills and an introduction to computational thinking in biological systems. |
| Year 2 | Core Integration | Hands-on training in Artificial Intelligence and Data Science, molecular biology and genetic engineering, biochemistry, bioinformatics and computational biology, along with machine learning fundamentals for analysing biological data. |
| Year 3 | Advanced & Translational | Advanced learning in AI and Intelligent Systems, Genomics and Disease Biology, Gene Therapy and Genome Engineering, and Translational Medicine, along with regulatory and ethics frameworks, integrating AI with genomic sciences. |
| Year 4 | Application & Industry | Capstone research and innovation focused on Computational & Data Systems, AI, Bioinformatics & Digital Health Technologies, Genomics, Drug Discovery & Advanced Biotechnology, with Industry Exposure & Professional Practice, including a 8–12 month industry internship in biotechnology, AI healthcare, or research laboratories. |
The curriculum is designed around key interdisciplinary domains that integrate genetics, genomics, bioinformatics, precision medicine, translational genomics, and artificial intelligence. This structure enables students to analyse complex biological systems and develop advanced data-driven healthcare applications.
DNA structure, gene regulation, and genome organisation
Next-generation sequencing (NGS) technologiesVariant analysis and mutation detectionHuman genetics and mechanisms of genetic diseasesPopulation genetics and genome-wide association studies
(GWAS)
Biological database design and managementSequence alignment, genome annotation, and comparative
genomicsGenomic data analysis pipelinesMulti-omics data integration (genomics, transcriptomics, and
proteomics)Cloud computing and high-performance computing for biological
data analysis
Machine learning models for genomic predictionDeep learning for biological pattern recognitionAI-driven disease risk prediction and biomarker
discoveryNatural language processing for biomedical literature
miningExplainable AI for clinical and genomic decision
support
Genomic diagnostics and personalised medicineAI-assisted drug discovery and therapeutic target
identificationCancer genomics and therapeutic stratificationGene therapy and genome-editing technologies (e.g., CRISPR)
Clinical genomics, regulatory science, and ethical use of
genomic dataThe programme incorporates strong industry engagement and expert mentorship to ensure that students gain real-world exposure and develop career-ready skills.
Students are encouraged and supported to undertake internships with biotechnology companies, pharmaceutical organisations, AI-driven healthcare start-ups, and genomics laboratories, enabling them to gain practical industry experience.
The programme facilitates interactions and mentorship opportunities with professionals from genomics, bioinformatics, AI-driven healthcare, and drug discovery sectors.
Regular sessions conducted by domain experts are organised on emerging areas such as AI in precision medicine, genomic diagnostics, and drug discovery.
Students are provided with opportunities to work on applied problems and real-world datasets relevant to healthcare, diagnostics, and biotechnology innovation.
Structured industry interactions, expert-led seminars, and dedicated career guidance sessions are designed to prepare students for placements, higher education, and research careers, while strengthening their professional competencies, career awareness, and long-term progression opportunities.
For students interested in entrepreneurship, the programme provides structured guidance and ecosystem support to help transform innovative ideas in genomics and artificial intelligence into viable ventures.
Students develop a strong foundation in genetics, molecular biology, mathematics, and programming (Python), while gaining exposure to basic laboratory techniques in biological sciences.
Students develop an understanding of biological systems as data-driven processes and acquire foundational computational and laboratory skills.
Students gain hands-on experience in molecular biology, genomics, and bioinformatics tools, along with foundational exposure to artificial intelligence, data science, and machine learning for analysing biological datasets. Training includes bioinformatics workflows, genomic data analysis, and molecular biology laboratory techniques.
Students develop the ability to process and analyse genomic data using computational and bioinformatics approaches.
Students learn advanced concepts in artificial intelligence, including deep learning and large language models, along with genomics and disease biology, gene therapy and genome editing, precision medicine, and the regulatory and ethical aspects of biomedical research. The focus is on applying AI models to large-scale biological and genomic datasets.
Students develop the capability to build AI-based models for disease prediction, genomic analysis, and biological data interpretation.
Students undertake capstone research projects, advanced pathway and minor electives, and are provided with opportunities to engage in extended industry internships across biotechnology, healthcare, artificial intelligence, and research environments. The focus is on applying interdisciplinary knowledge to real-world problems and developing professional competencies.
Students develop the ability to translate artificial intelligence and genomics knowledge into practical solutions and emerge as industry-ready professionals prepared for careers in healthcare, biotechnology, and research.
Applicable fee per semester (₹ )
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Following are the details of criteria and scholarship amount applicable:
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Following are the details of criteria and scholarship amount applicable
| Percentage Slab | Scholarship amount (per semester) (in Rs.) |
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| CUET UG percentile equal to or more than 97 in atleast 2 of the mandatory subjects as per the eligibility of the programme |
50000 (i.e. 25% of Programme Fee) |
| CUET UG percentile equal to or more than 95 but less than 97 in atleast 2 of the mandatory subjects as per the eligibility of the programme |
40000 (i.e. 20% of Programme Fee) |
| CUET UG percentile equal to or more than 90 but less than 95 in atleast 2 of the mandatory subjects as per the eligibility of the programme |
30000 (i.e. 15% of Programme Fee) |
| CUET UG percentile equal to or more than 80 but less than 90 in atleast 2 of the mandatory subjects as per the eligibility of the programme |
20000 (i.e. 10% of Programme Fee) |
Candidates seeking admission to the B.Tech. Genetics and Artificial Intelligence programme must meet the following eligibility requirements:
Admission is based on LPUNEST or JEE Mains or CUET merit, subject to the fulfilment of the eligibility criteria.
It is a futuristic interdisciplinary program that combines Genetics, Genomics, Bioinformatics, and Artificial Intelligence to prepare students for next-generation careers in healthcare, biotechnology, precision medicine, and computational biology.
This program integrates Biology with AI, Machine Learning, and Data Science — a rapidly emerging field transforming healthcare and life sciences globally.
Students with 10+2 having English, Physics, Chemistry, and Mathematics or Biology or Biotechnology with minimum 60% marks and qualifying LPUNEST are eligible.
No. The program starts from the basics and gradually trains students in coding, AI tools, and computational biology.
Students will learn:
Graduates can work as:
Yes. The program includes immersive industry and research exposure with internship opportunities of up to 8–12 months.
Absolutely. The interdisciplinary nature of the program provides strong preparation for MS, PhD, and global research opportunities in Genetics, AI, Biotechnology, and Biomedical Sciences.
Yes. The program focuses heavily on hands-on learning through modern laboratories, computational tools, research projects, industry interaction, and capstone projects.
LPU offers:
Yes. AI is rapidly transforming genomics, diagnostics, drug discovery, precision medicine, and healthcare analytics worldwide, making this one of the most future-ready career domains.
Students graduate with expertise in both Life Sciences and AI — a rare and highly valuable combination demanded by modern biotech, healthcare, and research industries.
8–12 Months of Industry Internship Experience
Industry Mentorship from Genomics and AI Experts
Hands-On Experience with Genomic Data and AI Models
Deep Expertise in Genomics, Bioinformatics, and Artificial Intelligence
Global Career Pathways in Biotechnology and AI Healthcare
Innovation and Entrepreneurship Opportunities
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