Programme Overview
The Masters in Data Science with specialization in Biomedicine is a pioneering programme that bridges the worlds of data science, biology, and medicine through an exciting collaboration between Institute of Management Sciences, one of Khyber Pakhtunkhwa’s leading academic institutions and Precision Medicine Lab one of the foremost biomedical research laboratory.
As Big Data continues to dominate the landscape, recognized by employers and the World Economic Forum as a cornerstone of future industries, there is a pressing need for expertise that blends biomedical sciences and data analytics—especially in the post-COVID era. This degree is the first of its kind in the region, designed to give students a competitive edge through interdisciplinary learning and practical exposure to real-world challenges.
Agreement Signing Ceremony held at Lincoln Corner, IMSciences, Peshawar on June 13, 2024.
Seated (L-R): Dr Faisal Khan, Director, Precision Medicine Lab and Dr Usman Ghani, Director, IMSciences.
Standing (L-R): Dr Madina Shirdel, Dr Khurshid Qasim Marwat, Dr Muhammad Ali, Prof Naseer Ahmad (VC, CECOS University),
Mr Shafique ur Rehman (CEO, RMI), Mr Salman Ahmad.
The programme’s core values are grounded in delivering real-world, translational, and interdisciplinary education. Students will not only gain deep technical skills in data science but will also implement them in solving critical problems in biology and medicine. Our handpicked faculty, passionate about teaching, are committed to ensuring that graduates are capable of making an impact from day one.
Programme Structure
Total duration of programme: 2 years
Total number of semesters: 4
Total number of credit hours: 36
Breakdown of Courses based on Type
| Course types | Cumulative Credits |
| Core Courses | 9 |
| Specialisation Courses | 6 |
| Elective Courses | 10 |
| Research Thesis | 6 |
| Soft Skills Courses | 3 |
| Group Capstone Project | 2 |
Semester-wise Breakdown of Course
| Semester 1 | Credits |
| Core 1 | 2+1 |
| Core 2 | 3 |
| Elective 1 | 2 |
| Soft Skills 1 | 1 |
9 | |
| Semester 2 | |
| Core 3 | 2+1 |
| Special 1 | 3 |
| Special 2 | 3 |
| Elective 2 | 2 |
11 | |
| Semester 3 | |
| Research Thesis 1 | 3 |
| Elective 3 | 2 |
| Soft Skills 2 | 1 |
| Group Capstone | 2 |
8 | |
| Semester 4 | |
| Research Thesis 2 | 3 |
| Elective 4 | 2 |
| Soft Skills 3 | 1 |
| Elective 5 | 2 |
8 | |
| Total Credit Hours | 36 |
Course Details
List of Taught Courses
Core Courses (all mandatory)
- Introduction to Statistical Thinking and Data Analysis (2+1)
- Systems Biomedicine: tools and techniques (3)
- Patterns and Machine Learning (2+1)
Specialisation Courses (any two)
- The Cell: Form and Function (3)
- Ethics and Health Economics (3)
- The internet of living and non-living things (3)
Elective Courses (any four)
- Biodesign: Solving Real-life Problems (2)
- Innovation and Entrepreneurship (2)
- Modern History in Brief (2)
- The Reflective Scientist (2)
- Cancer Biology and Molecular Oncology
- Genomic Diagnostics and Screening Tests
- Molecular Epidemiology and Population Health
- Neural Sciences, Behaviour and Brain Patterns
- Introduction to Electronic Health Records
- Methods of Causal Inference
- Image Analysis in Biomedicine
- Accelerated Natural Languages
Soft Skills Courses (any three)
- Writing and Reviewing Medical Papers (1)
- Science Communication in the Digital Age (1)
- Data Visualisation (1)
- Research Methodology (1)
Research Thesis
Students will choose an independent thesis under the supervision of a faculty member after an open day during Year 1. The students will dedicate a substantial amount of their time to their research thesis (3 credit hours per semester III and IV). The Thesis will be assessed and graded by an internal and at least one external examiner followed by public defence.
Group Capstone Project
To develop their interpersonal and team science skills, each students will also be a part of a group project that consists of not more than 4 students. These will be inter-disciplinary projects aimed at applications of tools and methods for solving a real-life problem identified by the team.
The Ideal Student
The AI-Ready Clinician
You’re a doctor or dentist who has realized that the future of clinical practice is deeply intertwined with AI. The healthcare landscape is evolving fast, and you know that AI is capable of playing a crucial role in diagnosis, treatment, and patient care. Rather than waiting for change to happen, you're ready to be part of it. Before committing to a clinical specialization or diving into a PhD (for those who are research-savvy), you’ve chosen to pursue a Masters. This programme will fill the gaps in your understanding of the biology of disease and its associated datasets, while also teaching you how AI models work. You’ll learn not just how to deploy these tools in your practice, but also how to contribute to building the next generation of AI solutions for tomorrow's healthcare. This Masters will equip you with the knowledge and skills to move beyond simply using AI but you'll be ready to critically engage with it, improve it, and even innovate new applications that can transform patient care.
The 21st Century Biologist
You have a solid foundation in biotechnology, microbiology, genetics, or a related field. The lab has been your second home, but you also know that biology today isn’t just happening under a microscope. It’s unfolding in code, in datasets, and in algorithms. You understand that no modern wet lab experiment is complete without a bioinformatics analysis of existing datasets. From genomics to systems biology, data is at the heart of it all. Now, you’re ready to bridge the gap: math, statistics, coding. These are the tools that turn biological questions into computational ones. Maybe you're thinking about a PhD in a world-class leading institute, shifting to bioinformatics, or simply aiming to become a sharper, more data-literate biologist, this programme gives you the edge to evolve with the science.
The Data Scientist Reshaping Healthcare
Biological datasets, like genomics, are some of the fastest-growing data types in the world, doubling every 12 months. This makes it a very exciting problem, if we set aside the tremendous impact on human lives and that of our planet. For the research-driven computer scientist who’s not thrilled by the idea of staying in the local IT or freelancing scene, this Masters is the perfect stepping stone. It’s designed for the one who has his eye on global trends in AI and wants to land in a top tech firm or a leading PhD programme abroad. This programme will arm you with the knowledge and skills to dive deep into biological datasets, and will put you at the forefront of the AI revolution in healthcare.
Hallmarks of our Graduate
Throughout the programme, students cultivate the following core qualities that define success in the data science and biomedicine fields:
Data-Savvy Leaders
With a hard data science core, our graduates can play with any type of data and draw insights that can help decision making. But with expertise in data from biology and medicine, our graduates become unmatched leaders in their field who are set to shape the industry of tomorrow.
Well-Rounded and Articulate
Whether it's a 10 year old school boy, a 30 year old journalist or policy maker or 60 year old member of the public, we train our students to be articulate at all levels - inside the Lab and outside. We make sure our students develop their problem-solving, leadership, design and communication skills during their two years, before they enter a fast-paced job market of tomorrow.
Well-Informed and Responsible
Considering the historical, geographic, and socio-economic context that we find ourselves in, our graduates are well informed of the societal nuances and all the ethical, social and legal implications of the work they do in the research.
Lifelong Learners
We train life-long learners. We encourage students to keep that curious and creative child inside each one of us alive. This makes learning a lifelong trait and not an activity meant for a set period of time.
Impact-driven Passion
Every member of the Lab is driven by the pursuit of impact on the ground and on the poor and underprivileged that surround us. This commitment to service drives our pursuit of excellence. Our graduates are not swayed by temporary wins and the wrong incentives - numbers, quantities and rankings.
Bold and Entrepreneurial
Students are encouraged to fail fast and learn. And to have the courage to try new ideas or questions and do experiments which others might shy away from. This makes our graduates bold and entrepreneurial.
Integrity and Rigor
Our students and graduates espouse the highest levels of academic integrity and scientific rigour in their work as guided by our honour code. There is zero tolerance of any form of academic dishonesty, plagiarism or misconduct.
Confidence with Humility
Our graduates are full of hope and have a positive outlook towards life - all in the face of tough times. Their faith in our training and their command of the subject matter gives them confidence. But with humility. Humility that comes with the acknowledgment of how little we know.
Admissions
- Eligibility Criteria
Students who have a first-class bachelor’s degree in computer science, statistics, biotechnology, medicine, dentistry, or any equivalent/comparable major, with a minimum of 60% marks will be eligible to apply for the programme.
- Application Process
Applicants will first undergo a written test to demonstrate their knowledge and problem-solving skills. Shortlisted candidates will then be invited for interviews and a selection conference, where they’ll have the opportunity to showcase their passion, potential, and drive. All admissions are strictly merit-based.
- Class Size
The programme only offers admissions in Fall semester every year. Each class will be restricted to twenty four (24) full-time students.
- Application Deadline
Admissions for Fall 2025 will open in May 2025 and close by the end of June 2025. This is when most of our offers as well as financial aid decisions will take place.
- Entry Test: July 20, 2025
- Selection Conference: July 24, 2025
- Interviews: August 1, 2025
- Financial Aid: September 1, 2025
- Late admissions: September 1, 2025
We strongly encourage applicants to apply by the early deadline to be considered for the first round of offers and financial aid decisions.
Fee Structure and Financial Aid
- Fee Breakdown (2025–2027)
| Fee Component | Semester 1 | Semester 2 | Semester 3 | Semester 4 |
| Admission Fee | PKR 125,000 | – | – | – |
| Security (refundable) | PKR 12,000 | – | – | – |
| Tuition Fee | PKR 479,393 | PKR 567,481 | PKR 436,138 | PKR 436,168 |
| Total (payable per semester) | PKR 616,393 | PKR 567,481 | PKR 436,138 | PKR 436,168 |
| Programme Total (minus security) | PKR 2,044,180 |
- Financial Aid
The MS in Data Science, with specialisation in Biomedicine, is a world-class interdisciplinary masters programme and we are committed to making it accessible to talented students from all backgrounds. We believe it is critical for keeping our cohorts diverse and rich in perspectives.
The programme offers Financial Aid to students who submit an application at the time of their admission. All modes of Financial Aid cover Tuition Fee only and do not cover Admission, Security or Hostel costs. There are numerous ways students can support their studies including the following:
Merit Based Scholarships
Exceptional students may be offered tuition waivers (that can go up to 60%) based on their academic track-record and performance in their admission tests, interviews and selection conference. Students only need to indicate their interest in applying to a merit-based scholarship on their admission form.
Fee installments
Students may request their semester dues to be paid in easier installments through an application to the Financial Aid Committee at the time of accepting an offer for admission.
Need-based Scholarships
Students who wish to apply for a need-based scholarship that comes in the shape of a tuition waiver will be required to fill a form along with additional documents pertaining to their financial status at the time of accepting an admission offer but before the Financial Aid deadline.
Research Assistantships and Teaching Assistantships
Students may also apply for part-time TAships (with some faculty members on their courses) or RAships (on any of the research projects that have extra-mural funding). These opportunities can arise numerous times during the academic year and will be applied to on a case basis.
When to Apply for Aid?
Indicate your interest for financial aid while submitting your admission application.
Contact Us
For more information contact us at msds[at]precisionmedicine.pk
Phone
- +92 91 5838000
- PML General: 5232
- PML Admin: 5233
Frequently Asked Questions (FAQs)
What will be the programme timings and days?
The timings will be 9 am – 5 pm for 5 days a week Monday – Friday
Will there be hands-on and wet lab experience in the duration of the programme?
The degree offers a comprehensive experience which includes dry-lab work (data acquisition and analysis), wet-lab work in the laboratory and sometimes even hard-ware for example in a group capstone project.
What are the potential career opportunities for a masters’ in data science graduate?
Graduates of the Masters in Data Science with specialization in Biomedicine are equipped with a strong core in data science which enables them to draw actionable insights from any dataset in any field and solve problems. They will also have solid specialisation in datasets that are unique to biology (genomes, multiomes, networks, etc) and medicine (EMR, digital health, images and scans, signals, etc.). They are not only well placed to work in a government/policy, business/corporate or research/academic setting, but will also be equipped to spin out their startups.
What is the evaluation criteria?
All applications will be evaluated based on merit, and merit only. Admission will be offered to everyone on merit regardless of background, financial, or otherwise. Academic credentials are important, especially thesis work. Potential of impact in the field, demonstrated by prior work and past projects in different contexts, will be an advantage.
Are the exchange programmes being offered within Pakistan or globally?
This depends on the area and topic of projects that the students undertake. Exchange programmes will be offered at collaborating labs and companies in the country, and abroad based on scientific overlap.
Are there any opportunities for internships or industry collaborations during the programme?
The Lab offers opportunities to talented individuals every 3 months to polish their skills and experience an interdisciplinary culture. For individuals who perform exceptionally throughout the programme will also be offered permanent employment at either of the campuses.
Will the programme offer foundational or introductory sessions to help students from different fields understand each other’s areas of expertise?
Deficiency courses will be mandatory for some applicants based on their background.
How are the dual campuses utilized in the program, and what are the benefits of this setup?
A dual-campus opportunity integrates university-based classroom teaching and other resources such as libraries, co-curricular activities, student societies and incubation programmes, with a real-world research experience, allowing students to apply theoretical knowledge to actual problems outside the classroom.