The Integrated Science Lab (IceLab) (icelab.se) 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 some of the following areas: computational modeling, computational biology, computational physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining experience in these areas. Further, postdocs should have a deep interest in scientific collaboration between researchers using theoretical and empirical approaches. 

The six projects are: 

A.    Modeling RNA metabolism with applications in neuron development 

B.    Multiscale physiological response of reef-forming marine algae to environmental stress

C.     Financial Risk Management and Decision Making in Biodiversity Conservation

D.    How plant cell shape and tissue structure help cells stick together 

E.     DETERMINER - Determining appropriate monitoring frequency for phytoplankton

F.     Predicting bacterial protein expression during infection using machine learning

Detailed information on and specific requirements for each project is given below.

The IceLab Multidisciplinary Postdoctoral Program funded by Kempestiftelserna

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 approaches. 

We will welcome you to IceLab with genuine support by creative researchers working on a panel 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 postdoctoral fellowships are financed by Kempestiftelserna and are part of the IceLab Multidisciplinary Postdoctoral Program. A fellowship amounts to 708 000 SEK over two years. The scholarships are tax-free. Application deadline September 18, 2025. Start between January and April 2026 (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 to the decision date for the scholarship recipient. 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 some of the following areas: computational modeling, computational biology, computational physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining experience in these areas. 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.

Application

A full application should include:

1. 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),
2. A curriculum vitae (CV) with publication list,
3. Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained
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.
    

The application should be written in English or Swedish, and attached documents should be in Word or PDF format. The application should be registered via Umeå University’s e-recruitment system Varbi and submitted by the deadline 18th of September 2025.

Project descriptions, specific qualifications, and contact information

(A) Modeling RNA metabolism with applications in neuron development

The identity of a cell is largely determined by its RNAs. RNAs are short-lived molecules that quickly degrade after being translated into proteins. However, how do cells decide which RNAs to continue translating and which to degrade? Our current understanding suggests this results from a complex and not yet fully understood interaction between chemical tags attached to the RNA and protein complexes that deposit, remove, and interpret these tags. This project investigates a specific tag on messenger RNA (mRNA) known as N6-methyladenosine (m6A). m6A is critical, for instance, during neuron differentiation and stress response. By applying a model from epidemic spreading, you will develop a new mathematical model of actual molecular mRNA-protein mechanisms. By combining this model with experimental data, you will uncover how RNA-binding proteins “read” this tag to determine the mRNA’s fate. This exciting work connects molecular biology and mathematical modeling, and helps provide essential insights into development and disease.

The postdoctoral researcher will have the opportunity to:

• Explore how “reader” proteins determine RNA fates.
• Apply mathematical models from epidemiology to understand RNA metabolism.
• Perform stochastic simulations to analyze model behaviors.
• Fit the model parameters to empirical RNA expression and RNA-protein binding data.
• Predict outcomes of molecular perturbations.

As a postdoctor, you will have the opportunity to join two research groups. One group is part of the Department of Molecular Biology and focuses on epigenetic and RNA-based gene regulation (Aguilo Lab). The other group, based in the Department of Physics, develops mathematical models to understand the dynamics of a wide range of living systems, such as gene regulation (Lizana Lab). In this project, we look for a young researcher interested in small living systems who wants to learn how to create quantitative models based on molecular mechanisms. This postdoctoral scholarship is an ideal starting point for someone wishing to establish a future cross-disciplinary research lab that integrates theory and experimental research.  

Specific Qualifications for Project A

To qualify for the fellowship, the candidate should hold a PhD degree, or a foreign degree that is deemed equivalent to physics, mathematics, or molecular biology. But more importantly, the candidate should have experience in mathematical modelling or simulations, preferably of biological systems. We encourage candidates from diverse departments, such as physics, computer science, applied mathematics, computational biology, and bioinformatics. Also, apart from experience with modelling and programming, the candidate should have a strong interest in interdisciplinary research. This means processing empirical data and collaborating with experimentalists from molecular biology. The candidate must also be highly motivated and capable of working both independently and collaboratively within a research group. The candidate must be fluent in both oral and written English.

Contact Information Project A

Ludvig Lizana, Department of Physics, Umeå University (ludvig.lizana@umu.se)

Francesca Aguilo, Department of Molecular Biology, Umeå University (Francesca.aguilo@umu.se)

(B) Multiscale physiological response of reef-forming marine algae to environmental stress 

Marine photosynthesis supports almost all ocean life, especially in the coastal zone. Unfortunately, climate change and human activity are causing significant environmental change in the ocean, threatening ocean health. Marine heatwaves and coastal darkening are two important stress factors that have gained attention lately, however, their combined effects remain poorly understood. In this project, the postdoctoral fellow will quantify the biophysical stress response of red coralline algae to heatwaves and darkening. These morphologically complex seaweeds create highly biodiverse algae reefs around the world, but face extinction because of ocean environmental change. 

In this project, the postdoctoral researcher will have the opportunity to investigate coralline algae responses to these stressors, using a unique approach that combines ultrafast spectroscopy, single-cell spectroscopy, multicolour fluorescence and numerical modelling. This multidisciplinary approach will significantly advance our understanding about the resilience of coralline algae to projected environmental change, with unprecedented insight into the mechanisms of response and the variability within individual organisms. Support and training will be provided as required, depending on the candidate’s incoming expertise.

The postdoctor will be housed in IceLab and hosted by the Department of Ecology & Environmental Science, the Department of Physics and Umeå Marine Sciences Centre, supervised by a multidisciplinary team with complementing expertise in algal ecology & biogeochemistry, ultrafast spectroscopy and optics & biophysics.

Specific Qualifications for Project B

To qualify for the fellowship, the candidate should have a PhD degree, or a foreign degree that is deemed equivalent, in plant / algal physiology or experimental biophysics. The ideal candidate has skills in (photo)physiology and biological experimentation, with meriting experience in optical spectroscopies (including frequency and time domain absorption, fluorescence and / or Raman spectroscopies), and / or imaging or atomic force microscopy. Importantly, the candidate will be interested in pursuing research that addresses climate change and sustainable development challenges at the intersection of biology and physics.

Contact Information Project B

Heidi Burdett, Department of Ecology & Environmental Science, Umeå Marine Sciences Centre (UMF), Umeå University (heidi.burdett@umu.se)

Nicolò Maccaferri, Department of Physics, Umeå University (nicolo.maccaferri@umu.se)

Magnus Andersson, Department of Physics, Umeå University (magnus.andersson@umu.se)

(C) Financial risk management and decision making in biodiversity conservation

This project explores how financial decision-making tools, originally developed for managing investment risks in markets, can be applied to address real-world challenges in biodiversity and conservation policy.
The postdoctoral fellow will have the opportunity to delve into questions at the intersection of ecology, economics, and finance. For instance:

• How does risk aversion and the possibility of biological hedging shape conservation strategies?
• Can financial tools like biodiversity bonds or species-indexed futures promote better ecological outcomes?
• How should we account for uncertainty in the valuation of natural assets? 

This interdisciplinary research builds on real options theory and modern computational methods to assess dynamic, irreversible decisions under uncertainty. By blending tools from stochastic control, numerical simulation, and machine learning with ecological and economic models, the project offers a unique vantage point on biodiversity as a financial asset.

The postdoctoral researcher will have the opportunity to:

• Explore the impact of risk, ambiguity, and irreversibility on conservation strategies
• Build and analyze advanced mathematical models incorporating ecological, economic, and financial dynamics
• Apply machine learning and Monte Carlo techniques to simulate complex decision scenarios
• Contribute to a growing, interdisciplinary field that redefines biodiversity through the lens of finance 

This project is a collaborative effort between researchers in financial mathematics, resource economics, and ecology. It is ideally suited for scholars interested in using quantitative tools to tackle environmental challenges.

Specific Qualifications for Project C

To qualify for the fellowship, the candidate should hold a PhD degree (or a foreign degree deemed equivalent) in a relevant field such as mathematics, economics, finance, ecology, biology or physics. The ideal candidate has a strong background in mathematical modeling and computational techniques, and an interest in interdisciplinary applications related to environmental systems and decision-making under uncertainty.

Contact Information Project C

Christian Ewald, Department of Mathematics and Mathematical Statistics, Umeå University (christian.ewald@umu.se)

Tommy Lundgren, Department of Forest Economics, Swedish Agricultural University (SLU), Umeå  (tommy.lundgren@umu.se)

Micael Jonsson, Department of Ecology and Environmental, Umeå University (micael.jonsson@umu.se)

Kevin Kamm, Department of Mathematics and Mathematical Statistics, Umeå University (kevin.kamm@umu.se)

(D) How plant cell shape and tissue structure help cells stick together

How do cells actually stick to each other? Multicellular organisms maintain their multicellularity thanks to cell-cell adhesion. This is in principle mediated by adhesive bonds between cells. Here we propose to study the added contribution of cell shape and tissue topology as intrinsic properties that can minimize stress and hamper fracture propagation at cell-cell interfaces, contributing to adhesion maintenance and tissue integrity. In turn, we envision that knowledge acquired will broadly extend our understanding of the contribution of heterogeneous patterns and shapes to material robustness.

The postdoctoral researcher will have the opportunity to:

• Study the principles of plant cell adhesion and tissue biomechanics.
• Use microscopy image processing tools and software.
• Use, refine and develop finite element simulations frameworks.
• Optionally develop experimental lab skills including plant growth, sample preparation and 3D confocal microscopy.

This postdoctor will be housed in IceLab and hosted by Department of Plant Physiology and supervised by a multidisciplinary team with complementing expertise in cell-cell adhesion and photonic techniques to study biological processes.

Specific Qualifications for Project D

To qualify for the fellowship, the candidate should have a PhD degree, or a foreign degree that is deemed equivalent in computer science or biology. The ideal candidate has either a PhD in computer science (or related) with applications to biology, or a PhD in Biology, with a solid component of computer science.

Contact Information Project D

Stéphane Verger, Department of Plant Physiology, Umeå University (stephane.verger@umu.se)

Magnus Andersson, Department of Physics, Umeå University (magnus.andersson@umu.se)

(E) DETERMINER - Determining appropriate monitoring frequency for phytoplankton

Join the DETERMINER project and apply your mathematical and statistical skills to explore a crucial issue impacting assessment in aquatic systems: phytoplankton monitoring frequency.

Phytoplankton constitute the base of aquatic ecosystems, and their importance is such that European directives govern their environmental status. Phytoplankton can experience short-term change (hourly scale), while currently, most monitoring programs have fortnightly or lower resolution. This creates a mismatch between the rate at which phytoplankton change status and our ability to detect that change promptly. How much information is lost through this depreciated sampling frequency remains unknown. DETERMINER aims to determine the optimal sampling frequency for detecting externally driven phytoplanktonic change while also providing autonomous solutions to optimise the cost of monitoring programmes. 

We’re looking for a postdoctoral researcher to join this effort, combining tools from statistical learning, sparse data analysis, and time-frequency analysis to better understand how sampling frequency affects what we can detect in the data. Using high-resolution European and Baltic datasets, the project will tackle two key goals:

1. To detect optimal sampling frequency based on high-frequency monitoring programs
2. To qualify the detectability of extreme events: marine heatwaves and phytoplankton blooms in a context of sampling frequency.

This postdoctor will be placed in IceLab and connected to UMF and MMS. Their administrative home will be MMS. You will work with a supportive, multidisciplinary team with expertise in monitoring, modelling, and statistical tools. You will also have the opportunity to join monitoring coastal campaigns and fieldwork in the Gulf of Bothnia to better understand how monitoring programs operate.

Specific Qualifications for Project E

To qualify for the scholarship, the candidate should have a PhD degree, or a foreign degree deemed equivalent in one of the following fields: Phytoplankton Ecology, Marine Biology, Mathematical Statistics, Signal Analysis, Dynamic Systems, or a comparable field. The ideal candidate has strong skills in building and implementing statistical models. The applicant should have documented knowledge of statistical learning with sparsity and time-frequency analysis. Documented experience with marine biology and phytoplankton ecology is highly meriting. The applicant additionally needs to have excellent skills in modern computer programming languages such as C++, Python, MATLAB or R.

We look for candidates who enjoy collaborating in interdisciplinary teams and are good at communicating science in English to researchers from different backgrounds – experimenters, engineers, and theorists. The candidate should have a solid drive to move their project forward independently and be able to think critically.

Contact Information Project E

Léon Serre-Fredj, Umeå Marine Science Centre (UMF), Umeå University (leon.serre-fredj@umu.se)

Jun Yu, Department of Mathematics and Mathematical Statistics, Umeå University (jun.yu@umu.se)

(F) Predicting bacterial protein expression during infection using machine learning

How can we predict bacterial protein expression during infection to uncover how bacteria survive and resist antibiotics?  When bacteria infect us, they face intense stress. To adapt and persist, they produce proteins that help them manage hostile conditions, evade immune defenses, and resist antibiotics. Identifying these proteins is crucial to understanding infections. However, our proteins outnumber them in tissues, and current experimental techniques fall short. This project presents an opportunity to address these challenges using powerful computational approaches. By combining unique transcriptomic and proteomic data with novel strategies in machine learning and systems biology, we aim to build models that reveal bacteria’s hidden strategies during infection.

As a postdoctoral researcher, you will have the opportunity to:

• Explore how bacterial gene expression translates into protein production under infection-related stress
• Develop and apply machine learning methods to predict protein levels from transcriptomic data
• Identify regulatory mechanisms that explain mRNA-protein mismatches
• Construct computational models that uncover essential bacterial functions during infection

The project capitalizes on the PATHOgenex RNA and Protein Atlases, developed by the Avican Lab, along with extensive clinical and experimental datasets. You will join a collaborative environment and work closely with research groups specializing in microbiology (Avican Lab), machine learning (Erdem Lab), and network science (Rosvall Lab), with opportunities to deepen your expertise in integrative omics, data-driven life science, and translational infection research. This scholarship is ideal for researchers eager to use computational tools to uncover hidden mechanisms of microbial life under stress and who would like to grow in a supportive, interdisciplinary environment.

Specific Qualifications for Project F

To qualify for the fellowship, the candidate should hold a PhD degree in one or more of the following fields: computational biology, systems biology, microbiology, bioinformatics, or related areas. The ideal candidate has experience in omics data analysis, machine learning, and an interest in infection biology.

Contact Information Project F

Kemal Avican, Department of Molecular Biology, Umeå University (kemal.avican@umu.se)

Cemal Erdem, Department of Medical Biosciences, Umeå University (cemal.erdem@umu.se)

Martin Rosvall, Department of Physics, Umeå University (martin.rosvall@umu.se)