M.Tech in Biomedical Data Sciences
A two-year postgraduate programme at the intersection of life sciences and data science.
M.Tech in biomedical data sciences overview
The programme integrates biological sciences with data science to prepare graduates to analyse complex biomedical data for research and healthcare applications. Students experience:
Biomedical data foundations
Learning in statistics, computational biology, programming and data management for biomedical datasets.
Machine learning in healthcare
Application of machine learning to clinical trials, biomedical imaging and healthcare decision-making.
Hands-on work with real data
Workshops using genomics, imaging and digital health data, from cleaning to interpretation.
Interdisciplinary research exposure
Systems biology, network modelling and research projects focused on real biomedical problems.
Programme details
About
The M.Tech in Biomedical Data Science provides an interdisciplinary curriculum designed to train students to analyse and interpret large, complex biomedical datasets from multiple sources. The programme equips students with the skills required to solve challenging problems in healthcare and life sciences through advanced data analysis and computational approaches.
The Centre for Life Sciences at Mahindra University is developing a collaborative research and teaching environment where students and faculty work together to create innovative technologies and analytical methods. These efforts aim to improve disease diagnosis and treatment while reducing healthcare costs through data-driven insights.
Why M.Tech in Biomedical Data Science?
The rapid growth of biomedical data has created a strong demand for professionals capable of analysing and interpreting this information. As noted by experts in the field, the increasing availability of biomedical datasets requires highly skilled data scientists who can translate data into meaningful improvements in healthcare.
Over the past decade, biomedical data has expanded significantly due to advancements in:
- Large-scale genomic sequencing
- Medical imaging technologies
- Mobile health (mHealth) data
- Clinical and electronic health records
Simultaneously, advances in computing power and storage have made it possible to analyse this data using advanced statistical techniques, machine learning models and biological simulations. These developments have led to the emergence of biomedical data science as a critical field that integrates biology, medicine, statistics and computing.
While leading universities globally already offer specialised programmes in biomedical data science, such programmes are still rare in India. This programme aims to address that gap by training the next generation of professionals capable of advancing biomedical research and healthcare innovation.
Through this programme, the Centre for Life Sciences seeks to develop expertise in biomedical data science and support research across areas ranging from basic biological research to clinical investigation.
| Course | L-T-P | Credits |
|---|---|---|
| Computational Biology | 3-0-0 | 3 |
| Statistics for Biomedical Data Science | 3-0-2 | 4 |
| Python Programming | 2-0-2 | 3 |
| Linux Workshop | 0-0-2 | 1 |
| Data Management and Engineering | 3-0-0 | 3 |
| Workshop in Data Visualization | 0-0-2 | 1 |
| Course | L-T-P | Credits |
|---|---|---|
| Machine Learning for Biomedical Data Science | 3-0-0 | 3 |
| Clinical Trials: Design & Analysis | 3-0-0 | 3 |
| Algorithms in Biomedical Data Science | 3-0-0 | 3 |
| Biomedical Imaging | 3-0-0 | 3 |
| Workshop in Genomics Data Analysis | 0-0-2 | 1 |
| Elective I | 3-0-0 | 3 |
| Course | L-T-P | Credits |
|---|---|---|
| Digital Health Informatics | 3-0-0 | 3 |
| Systems Biology & Network Modeling | 2-0-2 | 3 |
| Research Project – I | 0-0-12 | 6 |
| Elective II | 3-0-0 | 3 |
| Course | L-T-P | Credits |
|---|---|---|
| Research Project – II | 0-0-32 | 16 |
Eligibility
Applicants may hold any of the following degrees:
- B.E. / B.Tech, B.Sc. (Engineering), B.Sc. (four-year programme), M.Sc., M.C.A., MBBS, BDS, B.Pharm., B.V.Sc.
Minimum academic requirement
Applicants must have:
- Minimum 60% aggregate marks, or
- First-class qualification as defined by the awarding university, or
- CGPA / CPI of at least 6.0 on a 10-point scale, or an equivalent grade under other grading systems.
Potential employers
Graduates of the programme may find opportunities across research organisations, healthcare companies, pharmaceutical firms, consulting companies and technology service providers.
Core research and pharmaceutical companies
- Eli Lilly
- AstraZeneca
- Takeda
- Pfizer
- Merck
- Johnson & Johnson
- Novartis
- Corteva Agrisciences
- Sanofi
- Bristol Myers Squibb
- GSK
- Novo Nordisk
- Abbott
- Siemens Healthineers
- Boehringer Ingelheim
Research services and analytics companies
- Clarivate
- Elucidata
- Nimble Clinical Research
- IQVIA
- Evalueserve
- LabCorp
- Quantium
- WNS
- Cardinal Health
- Syneos Health
- US Pharmacopeia
- Axtria
- Ingenious Insights
- Caidya
IT and technology services companies
- Tech Mahindra
- Wipro
- TCS
- Infosys
- Cognizant
- Persistent
- Accenture
- HCLTech
Note: The list is indicative and not exhaustive.
FAQs
All core courses and projects are anchored in biomedical and healthcare data rather than generic applications.
Yes. The curriculum is designed to support both biology-focused and engineering-focused learners.
Students work with genomics, imaging, clinical trial and digital health datasets.
Graduates pursue roles in biomedical data science, bioinformatics, health analytics and research.
Yes. The final year focuses on research projects and thesis work, supporting doctoral pathways.
