Markowetz Group
Programme overview
We are excited to offer an opportunity for Year 12 students to gain hands-on experience with the Markowetz Group, a research team that combines computational biology, data analysis, and machine learning to understand how cancer develops and evolves. Our work uses cutting-edge technology to analyse large datasets and uncover patterns that help us answer key questions about cancer, such as how tumours grow, how the surrounding environment affects cancer, and why cancer can behave differently in different patients.
If you are curious about computers, data, and biology, this placement will introduce you to the exciting field of computational cancer research.
What you will do
During the placement, students will have the chance to:
- Observe and participate in basic data analysis to explore real biological datasets.
- Learn how researchers use machine learning methods to detect patterns in cancer data.
- Gain an understanding of cancer genomics — how tumours change and adapt over time.
- See how computer programming is used to study biological questions (no prior programming experience is needed).
- Work alongside scientists to understand how data from patients can help identify differences in cancer types.
- Participate in group discussions and workshops to explore the connection between computational tools and solving real-world problems in cancer biology.
About the Lab
The Markowetz Group at the Cancer Research UK Cambridge Institute combines computational and experimental research to answer important questions about cancer biology, including:
- Early detection: How do we detect cancers earlier to prevent cancers and help patients live longer?
- Genetic changes: What are the key genetic changes that drive cancer and lead to treatment resistance?
- Patient variability: Why does cancer behave differently in different patients?
We use advanced machine learning and data analysis techniques to process and interpret large amounts of data from cancer experiments. By combining computers and biology, we aim to uncover insights that can lead to better cancer treatments and a deeper understanding of the disease.
What to expect
This placement is designed to give you an interactive introduction to computational biology and its role in cancer research. You’ll get a glimpse into how computers, mathematics, and biology come together to solve some of the biggest questions in science.
Hypothetical Activities Include:
- Data analysis: Working with example datasets to uncover patterns and trends in cancer research.
- Introduction to machine learning: Learning how computers “learn” to make sense of complex data.
- Cancer genetics: Exploring how tumours acquire changes over time and their importance.
- Programming basics: Observing how simple coding techniques can be used to analyze biological data (no coding background required).
- Visualizing data: Learning how to turn large amounts of information into clear graphs and charts that scientists can understand.
- Group discussions: Talking to researchers about how their work helps answer big questions about cancer biology and patient outcomes.
What you will gain
By the end of the placement, you will:
- Understand how computational biology is used to study cancer.
- Learn about machine learning and its role in identifying patterns in large biological datasets.
- See how data analysis and programming can help solve real-world scientific problems.
- Develop skills in problem-solving, data interpretation, and critical thinking.
- Gain insight into how combining biology and computer science can lead to innovative breakthroughs in cancer research.
If you’re interested in science, computers, and data—and how these fields can come together to answer life-changing questions—this placement will inspire you to explore the exciting and fast-growing world of computational biology!
Risk assessment
| List of task | High risk | Medium risk | Low risk | Control measures |
| Trip hazards | X | Work areas are clear of obstructions, no open computer cables are kept around on the floors. | ||
| Repetitive Strain Injury | X | Ergonomic peripherals are provided including chair. | ||
| Eye strain | X | Monitors at eye level will be provided with adequate lighting to the office. | ||
| Electrocution | X | All appliances are fully PAT tested so risk is minimal | ||
| Fire | X | Fire safety procedure will be demonstrated at the beginning of the placement including nearest fire exits and meeting point. Fire risks shall be cleared and removed. |