MSc thesis project available

MSc thesis on deep representation learning for brain organoids

Are you an MSc student in Computer Science, Physics, Maths, Bioinformatics, or a related discipline with strong coding/ML skills and an interest in biological questions? This thesis project might be interesting for you!

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The Project

In this project, we want to use different data modalities to learn faithful representations of cellular states and dynamics during human brain development. Using combinations of deep learning, probabilistic modeling, and (neural) optimal transport, we want to better understand how cells execute complex decisions. We will develop new computational methods and apply them to in-house generated datasets.



Understanding the behavior of biological cells requires robust quantitative representations of cellular state. Once we have such representations, we can use them to understand how cells make decisions, for example, how a stem cell executes the “building plan” to generate an entire human body.

In our context, we’re interested in the formation of the human brain - a hugely complex process involving many different types of cells. We generate our own data in the lab, where we use reprogrammed stem cells to form mini-brains in a dish - so-called “brain organoids”. These brain organoids resemble the actual human brain in a number of important aspects - for example, they contain many different types of neurons and other brain cells. However, the major advantage of these brain organoids is that we can generate them at a large scale in the lab, to get enough data for machine learning models.

We perform different experiments on these brain organoids, which give us different data modalities, including sequencing and imaging data. Importantly, our experiments are precise enough to identify individual cells, and their molecular properties.

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Marius Lange
Marius Lange
Postdoctoral researcher

Interested in single-cell genomics and machine learning.