Three multidisciplinary postdoctoral fellowships (2 years)

The Integrated Science Lab (IceLab) jointly with several departments at Umeå University and SLU offer three postdoctoral scholarships that will be affiliated with one of six possible multidisciplinary projects. 

The ideal postdocs will have expertise in mathematics, machine learning, computational modeling, systems biology, molecular biology or an interest in obtaining experience in these areas. Further, postdocs should have a deep interest in scientific collaboration between researchers using theoretical and empirical approaches.

The IceLab Multi-disciplinary Postdoctoral Program

Umeå University is one of Sweden’s largest institutions of higher education with over 36,000 students and 4,100 faculty and staff. We are characterised by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison. Umeå University is also the site of the pioneering discovery of the CRISPR-Cas9 genetic scissors – a revolution in genetic engineering that has been awarded the 2020 Nobel Prize in Chemistry. 

The under-explored terrain between traditional disciplines is full of fascinating and impactful research questions. At IceLab, we promote and facilitate transdisciplinary collaborations – with a focus on cutting-edge research that integrates theoretical, computational, and empirical work.

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 and are part of the IceLab Multidisciplinary Postdoctoral Program. A fellowship amounts to 2 years funding: 28,000 SEK per month.  The scholarships are tax-free. Application deadline September 21, 2023. Start winter/spring 2024 (exact start date according to agreement).

Formal Qualifications

To qualify as a postdoctoral scholarship holder, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirements must be fulfilled no later than at the time of the decision about scholarship recipient.

Priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area.

Candidates should have experience in computational, machine learning, quantitative modeling, systems biology, molecular biology or an interest in learning those skills. Personal qualities such as collaboration, communication, strong drive and motivation, critical thinking abilities, creativity and analytical skills are essential. You should be able to take on the research independently and as part of a team. Good knowledge of oral and written English is required.

Six Possible Projects

Light variability as a driver of organismal resilience to environmental change

Photosynthesis supports almost all of ocean life, so the underwater light environment is tremendously important. This project will investigate light harvesting in red algae from both a theoretical and experimental perspective, using multiphysics modelling and single-cell spectroscopy. This will allow us to predict light harvesting at cell to habitat scales, providing important new insight into environmental resilience, which can subsequently be used to inform marine conservation and ocean sustainability strategies. Click to Read Full Description

Deciphering infection-related epigenetic dynamics to explain the variability of human susceptibility to infections with respiratory pathogens

We have found that Tuberculosis (TB) and COVID-19, two major pandemics of our time with highly variable infection susceptibility, leave epigenetic marks on our genome. However, the origin, dynamics, impact on severity, and potential for long-term effects such as long-COVID-19 syndrome remain unknown. As part of an interactive team, the postdoc will gain experience in our extensive longitudinal biobanks, machine learning tools, and higher-order network models, helping analyze unique clinical data, decode complex epigenetic dynamics, and predict patient outcomes.

 Click to Read Full Description

Modelling ecological sustainability and economic viability of multi-trophic farming for Nordic latitudes

The project aims at developing a mathematical model of a multi-trophic, circular indoor farming system to explore its dynamical behaviour under different environmental and economic scenarios. The adaptive scaling and steering of inputs, outputs and flows through the network will be treated as an optimization problem to provide insights into the feasibility, robustness, and economic viability of such a food production system. The project requires skills in mathematical modelling and programming, and a basic understanding of biological processes in an ecosystem. Click to Read Full Description

Dissection of the cell shape acquisition mechanisms in plants

We hypothesize that the epidermis morphogenesis in plants is regulated by mechanical and/or chemical signals emerging from the cuticle layer. We aim to unravel crucial aspects of cell shape and cell fate determination by investigating the roles of mechanical and chemical signals derived from the cuticle, in pavement cell distribution and coordination in Arabidopsis leaf epidermis. Click to Read Full Description

Resolving microbial genomes in complex communities at the single-cell level

A fundamental challenge in microbiome research involves determining which organisms are part of a given microbial community. In this project, we will develop a high-throughput method, which can reconstruct whole microbial genomes from microbiome samples at the single-cell level. Click to Read Full Description

Outer membrane tethering in Gram-negative bacteria

The cell envelope of bacteria provides structural support and protects the cell from environmental stress. Gram-negative bacteria are known to covalently link their outer membrane to the peptidoglycan cell wall. Yet, the proteins involved in this tethering are largely uncharacterized. This project aims at identifying the mechanisms by which Gram-negative bacteria connect the outer membrane and the peptidoglycan using high throughput proteomics on a collection of phylogenetically diverse species. We are looking for a candidate that has a strong background in microbiology, molecular biology and/or biochemistry, and an interest in working in cell wall biology and proteomics.Click to Read Full Description

Application

A full application should include:

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

Submit your application as a PDF marked with the reference number FS 2.1.6-1347-23, both in the file name and in the subject field of the email, to medel@diarie.umu.se. The application can be written in English or Swedish. Application deadline is 21 September 2023. 

https://www.umu.se/jobba-hos-oss/stipendier/6-1347-23/

We look forward to receiving your application. 

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