International PhD Call 2027

Lab of Fly Sleep - Supervisor Sha Liu

Sleep is defined at the behavioral level, and several correlations with network dynamics have been identified. However, exactly what sleep does to neurons, glial cells, and synapses remains largely unexplored. My lab uses both Drosophila and mouse models to investigate these questions. The candidate will explore projects aligned with this theme.

Funding: Funding is available to support the start of the position. The candidate is expected to apply for an independent fellowship to secure longer-term funding.

Contact: Sha Liu

Find out more about the lab here.

Lab of Neuronal Communication - Supervisor Patrik Verstreken

Parkinson’s disease is a common but very complex neurodegenerative disease.  There are several monogenic causes of disease but also genetic variation in the genome increases risk to develop idiopathic Parkinson’s disease.  It is not known how risk variants interact and synergize and how their combined action affects key cellular processes such as lysosome- mitochondrial- and vesicle trafficking-function to the detriment of dopaminergic neuron survival.  We have developed advanced screening methodologies based on CRISPR technology in combination with high throughput guide RNA detection and you will use this technology to determine key genetic interactions that drive risk in Parkinson’s disease.  This work will pave the way to understand idiopathic disease (the majority of cases) and identify key interception nodes to protect dopaminergic neuron survival. 

Funding: Funding is available to support the start of the position. The candidate is expected to apply for an independent fellowship to secure longer-term funding.

Contact: Carles Calatayud Aristoy

Find out more about the lab here.

Lab of Neural Circuits of Vision - Supervisor Karl Farrow

To determine how midbrain circuits have adapted to different ecological niches we compare two species of Peromyscus (Deer mice and Beach mice), which show distinct responses to approach predators. This work will combine behavior, optogenetics, Neuropixels and circuit tracing to determine if the role individual brain structures in the early visual system play the same in each species. This work will exploit modern molecular and circuit neuroscience tools (Rabies tracing, AAV expression of opsins, Neuropixels) to determine how elements of the early visual system evolved in response to different environmental pressures. 

Funding: Funding is available to support the start of the position. The candidate is expected to apply for an independent fellowship to secure longer-term funding.

Contact: Karl Farrow

Find out more about the lab here.

Lab of Cortical Processing - Supervisor Vincent Bonin

Description of the lab
How does the brain transform sensory information into perception and behavior—and how are these computations altered in neurodevelopmental disorders?

We are looking for a computationally oriented PhD student to develop and apply AI and machine-learning approaches to large-scale neuroanatomical, neural activity, and behavioral datasets.

Our lab studies how distributed brain circuits support visual and multisensory processing, perception, learning, and behavior. We combine advanced imaging, electrophysiology, quantitative neuroanatomy, and behavioral experiments in mice to generate rich datasets spanning brain structure, neural activity, and behavior. We also investigate how these circuits are altered in neurodevelopmental disorders, including SYNGAP1-related disorders.

Description of the project

The PhD student will use and develop computational approaches to uncover structure in complex neuroscience datasets.

• AI and computer vision for neuroanatomy — mapping cells, projections, and circuit organization from large-scale imaging data
• Machine learning for behavior — extracting behavioral states and sensory responses from video and high-dimensional behavioral data
• Neural population analysis — understanding how distributed cortical and subcortical networks encode visual and multisensory information
• Multimodal data integration — linking anatomy, neural activity, and behavior across animals and experimental conditions
• Computational neurodevelopment — identifying circuit and behavioral phenotypes in genetic models of neurodevelopmental disorders, including SYNGAP1

The emphasis will be on computational analysis and method development, working closely with experimental neuroscientists who generate the data.

Who are we looking for?
We welcome candidates from computer science, AI/machine learning, computational neuroscience, data science, engineering, physics, applied mathematics, or related quantitative fields.
Strong Python and quantitative skills are particularly important. Experience with deep learning, computer vision, statistical modeling, or large-scale data analysis is an advantage. Previous neuroscience experience is not required—we are especially interested in computational candidates excited to apply their skills to fundamental questions about the brain.

Research environment
The Bonin Lab is part of the VIB–KU Leuven Center for Neuroscience in Leuven, Belgium. The project will involve close collaboration with labs at the VIB.AI Center for AI & Computational Biology, bringing together expertise in experimental neuroscience, machine learning, and computational biology.
The position offers the opportunity to develop new computational approaches while working with state-of-the-art datasets from two-photon and widefield imaging, electrophysiology, quantitative neuroanatomy, and high-dimensional behavioral recordings.

Funding: Funding is available to support the start of the position

Contact: Vincent Bonin

Find out more about the lab here.