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Open position: Postdoc in machine learning

Postdoc in Machine Learning: Semantic analysis of single-cell data
Single-cell analysis is the current state of the art in biology - tissue samples such as cancer can be separated into individual cells, which are then measured at depth using sequencing. Enormous amounts of data are produced, enabling precise investigation of the content of the tissue. The bottleneck is now the researcher, and exploring a single dataset can take up to one year.

In this project we will use text analysis to guide the analysis. Over 500 000 articles have been published about just T cells, and using modern machine learning we will extract the biological knowledge. The researcher will be able to use the system in several ways; (1) asking why cells behave like they do, (2) ask which cells correspond to a certain behavior or (3) organize summaries by descriptions of certain biological phenomena. The success of this outcome will greatly aid basic research. However, single-cell is increasingly used for advanced diagnostics, and being able to quickly analyze data is of essence for bringing this method to the clinic.

problem overview
Our approach will use generative large-scale language models, fine-tuned over the available open access literature, curated literature-gene linkages, and other large datasets. The language model will then integrate with a Variational Autoencoder (VAE) model that captures the statistical properties of the single-cell data.

The candidate postdoc should be familiar with transformer models, ideally the GPT family. Furthermore, knowledge of clustering and VAEs is a merit, as is experience of computational linguistics. Willingness to learn basic biological concepts is key to success. The candidate will work in an interdisciplinary team at Umeå University under supervision of Johanna Björklund (department of computing science) and Johan Henriksson (department of molecular biology and MIMS).

For more information about our research groups and contact details:
For more information about our environments:

Emmanuelle Charpentier took the Nobel Prize in Chemistry

Emmanuelle has been awarded jointly with Jennifer Doudna the 2020 Nobel Prize in Chemistry for discovering the groundbreaking CRISPR-Cas9 gene editing technology. She is a former group leader at MIMS, honorary doctor at Umeå University and former visiting professor at UCMR.

Movie by Knut and Alice Wallenberg Foundation (

MIMS is characterized by
ECharpentier about MIMS 2015 1

Emmanuelle Charpentier, Alumna at MIMS, Director of the Max Planck Unit for the Science of Pathogens, Berlin, Germany.

Link to the Emmanuelle Charpentier Lab

Battling antibiotic resistance

movie by Knut and Alice Wallenberg Foundation, with participation of scientists from MIMS and UCMR:
Or watch the original movie on:

Research about infectious diseases:

Oliver Billker in movie of Knut and Alice Wallenberg Foundation:
Or watch the original movie on:

Emmanuelle Charpentier
about her research at MIMS

footer all slides 2014-02-06

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