Students interested in carrying out a Master research project in the EPFL Laboratory of Sensory Processing should contact Carl Petersen and Sylvain Crochet to discuss possible opportunities. We offer a wide range of projects involving experimental work, data analysis and computational neuroscience. Some specific open projects are listed below:
Project 1: Analysis of animal behaviour during learning (Start in 2025, Suitable for Master thesis project full time for at least one semester / 4 months) – In laboratory settings, video filming is used to monitor movements during behavioural paradigms. Machine learning tools, such as DeepLabCut, an open-source software tool for pose estimation, have facilitated the analysis and quantification of behaviour. Recent work has emphasized the influence of movement on neural activity as well as the richness of movement patterns that animals exhibit. The goal of this project is to explore and quantify orofacial movements of head-fixed mice that perform an associative learning task. More precisely, we seek to model possible relationships between movements and mouse decisions as the mouse learn the association of a sensory stimulus with a reward on a trial-by-trial basis.
We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate rich behavioural data and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with machine learning, statistics, data visualization and an interest for neuroscience and behavior.
Project 2: Analysis of brain-wide neuron-to-neuron interactions during learning (Start in 2025, Suitable for Master thesis project full time for at least one semester / 4 months) – The mouse brain is a complex network of millions of neurons, each receiving and projecting signals to hundreds of other neurons. Recent advances in recording technologies allowed us to measure thousands of single neurons simultaneously during an associate learning task. Our unique large-scale dataset is amenable to the analysis of the concerted activity of many neurons in various brain regions during behaviour. The goal of this project is to quantify single-neuron interactions at a brain-wide scale, and explore how learning may shape these interactions.
We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate large datasets of spiking activity and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with signal processing, statistics, data visualization and an interest for neuroscience and behavior.
Project 3: Analysis of brain-wide neuronal selectivity during learning (Start in 2025, Suitable for Master thesis project full time for at least one semester / 4 months) – Understanding how individual neurons encode information is fundamental to deciphering brain function. Single-neuron measures of selectivity provide a mean to characterise how neurons respond to particular stimuli or task-related events, providing insights on the neural mechanisms underlying behaviour. The goal of this project is to quantify and model single-neuron measures of selectivity at a unique brain-wide scale, and explore how learning may shape this selectivity.
We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate large datasets of spiking activity and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with GLMs, machine learning, statistics, data visualization and an interest for neuroscience and behavior.