IceLab Multidisciplinary Postdoctoral Fellowships

3 Postdoctoral fellowships (2 years) in Bacteria cell wall systems biology, soil pore architecture, and image analysis of wood formation

Application deadline:

August 31, 2021

The Integrated Science Lab (IceLab) jointly with the Department of Forest Genetics at the Swedish University for Agricultural Sciences and the Departments of Physics, Molecular Biology, Plant Physiology, and Ecology and Environmental Sciences at Umeå University, seek three postdoctoral fellows, one to each of the following three multidisciplinary projects: (1) bacterial cell wall systems biology, (2) changing Arctic soil pore architecture in the tundra, and (3) emergence of interconnected networks of cells during wood formation.

The application window is open until August 31, 2021

Cutting-edge interdisciplinary research in IceLab at Umeå University

Umeå University conducts internationally recognized research in several areas, including applied mathematics, microbiology, epidemiology, public health, sustainability, economy, and artificial intelligence.

The under-explored terrain between traditional disciplines is full of fascinating and impactful research questions. Many researchers at Umeå University strive to explore this terrain by bridging disciplinary boundaries, especially those researchers who are associated with interdisciplinary research environments such as IceLab.

At IceLab, we promote and facilitate transdisciplinary collaborations – with a focus on cutting-edge research that integrates theoretical, computational, and empirical work. We combine mathematical and computational modeling expertise with a deep interest in working with empirical researchers.

We will welcome you to IceLab with genuine support by creative researchers working on a multitude of interdisciplinary problems. You will participate in both professionally and personally rewarding and entertaining activities aimed at training a new kind of researcher. A multidisciplinary team of researchers with complementary expertise will supervise each postdoc.

The two-year postdoc fellowships are financed by the Kempe foundations. Each fellowship amounts to 315 000 SEK per year plus 50 000 SEK in running costs. Start September 1 – December 31, 2021 (exact start date according to agreement).

Project descriptions

Project 1: Bacteria cell wall systems biology 

Bacteria are surrounded by a protective peptidoglycan cell wall. Hence, the enzymes responsible for making this wall are the main targets of our most successful antibiotics. However, emerging resistant bacteria are eroding the efficacy of our antibiotic arsenal. Identifying new genetic determinants of the bacterial cell wall as antibiotic targets is of highest international priority but requires an integrative, multidisciplinary approach.

We have recently pioneered unique systems-level analytical approaches of the bacterial cell wall with dedicated bioinformatic tools. The unprecedented high throughput of this technology makes it possible to profile the cell wall of bacterial mutant libraries under diverse culture conditions. The postdoc will get the opportunity to use a suite of systems biology and machine learning techniques to predict functional networks connecting cell wall chemical profiles with genetics and phenotypes for further mechanistic and physiological studies. Our ultimate goal is to identify the repertoire of proteins associated to cell wall synthesis and regulation in a number of important bacterial pathogens, determine the mechanisms that maintain cell wall homeostasis and those that promote plasticity, and ultimately find new and more effective antimicrobial therapies.

This postdoc will be based in IceLab, hosted by the Department of Molecular Biology, and supervised by a multidisciplinary team with complementing expertise in molecular infection biology, systems biology, and machine learning.

Project 2: Arctic soil pore architecture

The fate of deep soil organic matter in arctic soils represents one main uncertainty in models predicting feedbacks between terrestrial ecosystems and our planet’s climate. One existing theory postulate that the arrangement of soil pores, being the hotspot of biological activities, may regulate microbial activities, and thus, determine if this deep soil reservoir of organic matter becomes mineralized into greenhouse gases. This project aims to put this theory to the test and increase our understanding about what role soil-pore architectures play in regulating turnover of soil organic matter in the Arctic. Could alterations of soil pore systems cause an increase in greenhouse gas emissions from Arctic soils?

In this project, we value candidates who have experience modeling and analyzing complex networks using packages like NetworkX or self-written code. We search for a creative candidate interested in understanding differences in functionality between complex 3D structures formed by abiotic and biotic processes. The project will utilize expertise available at the Umeå Institute of Design to create 3D replicas of natural soil pore systems that will allow us to empirically validate theoretical models. Traveling to arctic regions will be optional.

This postdoc will be based in IceLab, hosted by the Department of Ecology and Environmental Science and supervised by a multidisciplinary team with complementing expertise in soil science, design and network modelling.

Project 3: Image Classification and Machine Learning to analyze wood formation using 3D tomography images

The demand for renewable wood-based products is constantly increasing as we move away from fossil resources-based products. Wood is the most important renewable resource for construction in the World, yet we still know very little about how it forms on the cellular level. A deeper understanding of the mechanisms of wood formation on the cellular level could lead to better trees with improved growth and mechanical properties for more sustainable biomaterial production.

To improve our understanding of how wood forms, this project aims to reveal the dynamics of cell rearrangement during wood formation. We will generate high-resolution time-lapse X-ray images of live aspen wood formation in 3D. Images containing thousands of cells in the wood formation zone, small cells with dense cytoplasm, that divides, grow and rearrange will, after that, be segmented from the images to assess cell descriptors. We will analyze cell shape, cell growth rate, anisotropy and cell-cell displacement to decipher how this network of dividing and expanding cells evolves to form the complex structure of wood from the segmented images. Thus, to solve the research question related to how wood forms on the cellular level we propose the following objectives:

  1. To develop new methods to assess accurate 3D segmentation of the cells from 3D X-ray images
  2. To analyze the morphological changes and the rearrangements of the network of cells that are taking place during wood formation

This will require expertise in image-processing but also data analysis to decipher the complex process of wood formation at the cellular level.

This postdoc will be based in IceLab, hosted by the Department of Forest Genetics and Plant Physiology (SLU), and the Department of Physics (UmU), supervised by an interdisciplinary team of researchers with expertise in developmental biology and computational physics.


To qualify for the fellowship, the candidate should have a PhD degree, or a foreign degree that is deemed equivalent, in one of the following fields: mathematics, computer science, physics, bioinformatics, biostatistics, mathematical statistics. In addition, the following fields particularly relevant to project 1 twill be considered: biology, biochemistry, microbiology.  A candidate who has completed their degree prior to this may be considered if special circumstances exist. Special circumstances include absence due to illness, parental leave or clinical practice, appointments of trust in trade unions or similar circumstances. The ideal candidate has strong skills in building and implementing mathematical and statistical models.

The applicant needs additionally to have excellent skills in modern computer programming languages such as C++, Python, MATLAB or R. Personal qualities such as collaboration, communication, strong drive and motivation, critical thinking abilities, creativity and analytical skills are essential. You should be able to perform research independently and as part of a team. Good knowledge of oral and written English is required.

In addition, candidates interested in project 1 should have basic microbiology knowledge and be passionate about using statistical methods and machine-learning algorithms to answer biological questions. Work experience with large-scale data analysis is a requirement.

In project 2, we value candidates who have experience modeling and analyzing complex networks using packages like NetworkX or self-written code.

Candidates interested in project 3 should have strong expertise in image processing and data analysis. Ideally, you have experience in machine learning and network analysis.


A full application should include:

  1. A cover letter summarizing your qualifications, your scientific interests, which project or projects you are particularly interested in, and your motives for applying (max 2 pages),
  2. A curriculum vitae (CV) with publication list,
  3. Certified copy of doctoral degree certificate,
  4. Certified copies of other diplomas, list of completed academic courses and grades,
  5. Copy of doctoral thesis,
  6. Copies of relevant publications,
  7. Contact information for at least two reference persons,
  8. Other documents that the applicant wishes to claim.

Submit your application as a PDF marked with the reference number FS 2.1.6-1435-21 for project 1FS 2.1.6-1436-21 for project 2, and FS 2.1.6-1437-21 for project 3, both in the file name and in the subject field of the email, to The application can be written in English or Swedish. Application deadline is 31 August 2021.

A copy of the application should also be sent to

Further Information 

Further information on project 1, contact Associate Professors Felipe Cava ( and Nathaniel Street (

For more information on project 2, contact Professor Jonatan Klaminder ( and Associate Professor Ludvig Lizana (

For more information on project 3, contact Assistant Professor Stéphane Verger ( and Associate Professor Magnus Andersson (


 We look forward to receiving your application. 

Apply by Email