MIMS - Open Positions/Thesis work

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.

Open position: PostDoc Project in In vivo efficacy of novel antimicrobials active against the bacterial pathogen Chlamydia

The Sixt lab at MIMS is looking for a postdoc to join the group and advance them at the field of Chlamydia research.

Project: The extensive use of broad-spectrum antibiotics is a major aggravator of the alarming spread of antimicrobial resistances. Moreover, it impacts patient health negatively by its devastating collateral effects on the microbiota. Hence, there is an urgent need for more selective treatment options. Using an innovative antimicrobial discovery approach, we have recently identified a set of compounds displaying narrow-spectrum activity against Chlamydia, a group of obligate intracellular bacteria that every year causes millions of cases of urogenital, ocular, and respiratory infections. The purpose of this project is to determine in vivo efficacy and selectivity of our most potent compounds.

Application deadline: 1 July 2022 or until a suitable candidate is found

Open position: Postdoc opportunities in the Henriksson lab

Picture: Johan Henriksson, MIMS group leader. Credit: Mattias Petterson.

The Henriksson lab is seeking two postdoctoral scientists to work on Project 1) in CAR T cells and CRISPR screening methods development, or on Project 2) in machine learning for single-cell data analysis. You will be based in the lab of Johan Henriksson (www.henlab.org). The Henriksson lab is based at the Department of Molecular Biology and is part of The Laboratory of Molecular Infection Medicine Sweden (MIMS), which is the Swedish node within the Nordic EMBL Partnership for Molecular Medicine.

Applications are reviewed as they come in.

Master student thesis projects in the Henriksson lab

Master thesis projects available in advanced molecular biology protocol development, of relevance for CAR T cells and malaria high-throughput screening! Hard working students who are prepared to roll up their sleeves and move out of their comfort zone are most welcome to apply :)

We are developing several protocols to improve the efficiency of pooled CRISPR or barseq screens, where extracting more information about each cell will boost the statistics. This is especially important when the cells are few (primary cells) or the expansion is uneven (in vivo screens). The project may also be combined with bioinformatics (python, R or java) based on student interests.

Keywords: Cloning, sequencing, inverse PCR, padlock probes, UMIs, mate pairing, HiC, ATACseq, RNAseq, CRISPR, cell culture, lentiviruses, bioinformatics

Illustration by Johan Henriksson.

Students are welcome

If you are interested to do an internship in a research group at MIMS and you know which group and topic should it be, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. (project coordinator at MIMS) and she will get in touch with the selected group leader. To see the research groups and their topics, go to https://www.mims.umu.se/groups.html .

PostDoc or PhD Position in the Henriksson Lab

Understanding CAR T cells through machine learning and advanced bioinformatics

Johan Henriksson, a MIMS group leader, is currently seeking a postdoctoral researcher or PhD student to dissect T cell regulation using single-cell methods and CRISPR screening. While the overall goal is to develop CAR T-cell technology, this position is geared towards sharpening our analysis methods. Of particular interest include better statistics for CRISPR-UMI pooled screens, gene regulation (ATAC-seq, HiC) and gene isoforms (RNA-seq).

Candidates who are strong in any of computer science, mathematics, statistics or machine learning are encouraged to apply. An interest in learning biology is essential and some basic insight will already help plenty. An overview of what we do, and contact information, can be found at http://henlab.org/