Professor Carolina Rezaval

Supervisor Details

Contact Details

School of Biosciences, University of Birmingham

Scientific Background

Research Interests

Our lab uses the fruit fly Drosophila to unravel the mechanisms underlying behavioural choices. By studying how the brain makes decisions at a genetic, cellular and circuit level, in an accessible experimental system, we aim to reveal fundamental principles that might be present across species.

Animals engage in daily activities that are essential for survival and reproduction, such as feeding, mating or fighting for resources.

How does an animal prioritise one behaviour over others? We know that cues conveying external information (e.g., threats from other animals, access to food) and internal state (e.g., fear, hunger) guide behavioural choices. However, how the brain selects specific actions remains unknown.

Our lab addresses this fascinating question using the fruit fly model, Drosophila. Fruit flies exhibit complex behaviours that are controlled by a relatively small brain. Thanks to sophisticated tools available in the fruit fly, we can interrupt specific genes, as well as visualise and manipulate individual neurons with great resolution. With these tools, we can study how the fly brain responds when there are conflicting options available, and how it chooses amongst them.

By studying how the brain makes decisions at a genetic, cellular and circuit level in an accessible experimental system, we aim to reveal fundamental principles underlying behavioural choices that might be present across species.

Research Groups

Rezaval Lab

Birmingham Fly Facility

Centre for Neurogenetics

Structural and Molecular Cell Biology

Supervision Style

In three words or phrases: student-centred, supportive, collaborative.

Provision of Training

I foster a collaborative and supportive learning environment where students receive structured guidance in the early stages of their PhD. Experienced postdocs and PhD students will work closely with you, offering hands-on technical training, while I focus on nurturing your critical thinking, soft skills, advice in methods, data analysis through individual meetings and lab discussions. As your confidence and expertise grow, I encourage greater independence, empowering you to take full ownership of your research as you develop and refine your own methods and approaches

Progression Monitoring and Management

I am dedicated to helping you reach your full potential, providing guidance and encouragement throughout your PhD. Together, we will set clear goals and regularly review your progress to ensure you stay on track. In the early stages, we will meet weekly, and we’ll adjust the frequency as needed. If any challenges arise, we will work together to find solutions, ensuring your steady growth and progress towards your aspirations. My goal is to empower you to confidently achieve the objectives you set for yourself.

Communication

I regularly communicate with lab members through Teams chats but maintain an open-door policy, always available to discuss any concerns—whether scientific or personal. I do not usually email team members during the weekend, but they are welcome to reach out if needed. I encourage open communication and am always here for guidance, to address any issues affecting progress, or simply to discuss science

PhD Students can expect scheduled meetings with me:

In a group meeting

Typically, once per week. But you can approach me spontaneously with a question, a problem, or anything you want to share.

In year 1 of PhD study

At least once per week. I’m always available for my students.

In year 2 of PhD study

At least once per week.

In year 3 of PhD study

At least once per fortnight.

These meetings will be face to face, and I am usually contactable for an instant response every working day.

Working Pattern

The timing of work in my lab is completely flexible, and (other than attending pre-arranged meetings), I expect students to manage their own time.

Notice Period for Feedback

I need at least 1 week’s notice to provide feedback on written work of up to 5000 words.

MIBTP Project Details

Prof Rezaval is supervising no projects this year.