10 Postdoctoral Fellowship at Umea University, Sweden 

An appointment as a postdoctoral fellow aims to give opportunities to new researchers to develop their independence in research after completing a PhD, and to create the conditions for further development. Your main task as a postdoctoral fellow will be to carry out research within one of the department’s research profiles in educational work and in connection to one of the research profile’s externally funded research projects. There are four research profiles in the subject: RECEUM: Early Childhood Education and Care research; PEPP: Education Politics and Policy; UngÖv: Education Policy and Youth Transitions; and, ARED: Teacher Education, digitalization. Teaching may also be part of your duties, mainly at undergraduate level, but may also occur at postgraduate level. 

The rapid development of autonomous systems, connected devices, and distributed applications poses several challenges in dealing with petabytes of data in diverse resource-constrained environments. Federated machine learning (FML) is a collaborative learning solution to handle these problems without sharing data with centralised servers. However, several emerging threats target FML training, learning, and inference to fail or mislead models at early learning rounds, particularly backdoor and bitflip attack and defence strategies under-explored in FML. These results jeopardize achieving trustworthy performance for any downstream tasks. Therefore, this project envisions developing and validating attack and defence strategies in federated learning for limited and diverse non-iid (independent identically distributed) data under non-standard and adversarial settings, which are ideally suited for edge AI infrastructures. These goals can be achieved by inducing unique features in federated learning algorithms such as robust training, model restoration, trustworthy device selection, secure learning and inference, fault-tolerance against failures and attacks, as well as resilient, fair and robust models. The ambition is to validate them in classical non-standard settings and apply them to solutions for constraint environments (e.g., the Internet of Things (IoT) and robotic arms). Potentially, teaching up to a maximum of 20% can be included in the work tasks.

Positive Energy Districts (PEDs) stand as a groundbreaking solution devised to expedite the process of decarbonization and facilitate the shift towards climate-neutral urban areas in Europe. These districts are designed to produce net-zero greenhouse gas emissions and actively manage an annual local or regional surplus production of renewable energy. However, achieving climate neutrality involves more than just technological advancements; the behavior of occupants emerges as a pivotal factor influencing the success of these initiatives. The overarching goal of this research project is to comprehensively explore the interactions between PEDs and occupants, aiming to cultivate a resilient climate-neutral transformation.

The position is intended to strengthen the IHBI lab and become a strong contributor to the research activities at Department of Applied Physics and Electronics.

The research project aims to identify molecular mechanisms underlying the onset as well as the remission of type 2 diabetes. For a long time, type 2 diabetes has been considered a chronic disease, but recent studies show that recovery is possible and associated with the ability to reduce fat (lipids) in our organs, where skeletal muscle and pancreas play a key role. Despite great efforts, important mechanistic information that could lead to improved treatment and prevention is missing. This project focuses on expanding the understanding of specific lipid mechanisms underlying the accumulation of bioactive lipid subtypes and their impact on insulin secretion and insulin sensitivity in skeletal muscle and pancreas. The project involves mass spectrometry-based analysis of metabolites and lipids and method development to validate findings from large-scale metabolomics and lipidomics analyses. These data will be combined with biochemical measurements of proteins and gene expression and functional measurements of insulin sensitivity and insulin secretion in human material, animal models and cell cultures.

Within the project, you will conduct experimental research work that you plan and evaluate in collaboration with the other researchers in the project. You will also be primarily responsible for writing scientific publications and presenting the obtained research data at scientific seminars/conferences.

The postdoctoral researcher is expected to pursue projects that focus on increased understanding of how vaccines stimulate high-quality B- and T-cell clones. Results from these studies will be coupled to national registry data to link molecular mechanisms to the protective effect of vaccines against infection or severe disease (for strategies used in the lab, see Kaku et al, Science 2023, Vikström et al, Lancet RHE, Blom et al, Lancet ID).

The project is based on two ongoing vaccine studies where longitudinal serum, plasma and PBMC samples have been collected since 2021. Of particular focus are capillary samples collected every three months from over 3000 elderly individuals since October 2021, as well as accompanying PMBC samples from a number of these. The initial focus of the project is to study the quality and quantity of T-cell memory after repeated vaccination, as well as to develop multiplex-based methods and study antibody-mediated immunity against respiratory infections in large population groups.

The Postdoc is expected to conduct independent research in population studies with focus on ageing. In addition to research, part of the job consists in contributing to the research environment by actively participating in the research seminar and other research activities such as grant application. Within the framework of the position, there is the opportunity to perform data analyses and write articles for publication in scientific journals based on existing data in ongoing research projects at CEDAR. Certain administrative tasks related to research activities might occur.

Satellite time-series indicate that Arctic vegetation productivity is increasing (greening), but also shows areas affected by productivity decreases (browning). These observations can be associated with vegetation changes, permafrost degradation or herbivory and other factors, but the causal links are often unclear. The aim of this project is to provide new knowledge on the impact of permafrost thaw and degradation on Arctic flora and fauna by assessing vegetation productivity, and to trace cascading effects on herbivores and local stake- and rightsholders, including issues of environmental contaminants. A key method will be the use of remote sensing data including unoccupied aerial vehicle (UAV) and satellite imagery and vegetation surveys. Fieldwork to collect UAV and ground data on vegetation properties is planned in three Arctic regions (Canada, Greenland and Svalbard).

You will mainly work with Arabidopsis and aspen (Populus) where the amount of different photosynthetic proteins have been modified using CRISPR and ”traditional gene technology”. These will be analyzed in the lab, in our ”phenotyping facility” and in the field using advanced techniques for studies of photosynthesis, including chlorophyll fluorescence, and growth. Work with other plant species may be included, and the project will be performed in collaboration with the technical platforms at UPSC, and other scientists involved in the project. 

The successful candidate is expected to work on the interrelation between pandemics and economics to improve integrated economic-epidemiological modelling to understand and project the societal costs of past and potential future pandemics, the cost and benefits of interventions to contain infections and reduce economic and educational losses, and the return-on-investment to pandemic preparedness.