21 Postdoctoral Fellowship at Uppsala University, Sweden

A position as postdoctoral fellow is available in Oskar Eriksson’s newly established research group at the Department of Immunology, Genetics, and Pathology. The group’s research is focused on translational studies of the complement system and the innate immune system (https://www.uu.se/en/department/immunology-genetics-and-pathology/research/vascular-biology/oskar-eriksson).
The current project will investigate endothelial cell-specific expression of complement factors and their function in endothelial activation and blood clotting. The project will use a combination of wet lab methods and analysis of publicly available RNAseq and proteomics datasets. It will also be possible to verify experimental findings in clinical materials.
Tasks in the project will include cultivation of endothelial cell lines and endothelial cells from various human tissues, as well as mapping and phenotypic characterization of expressed complement factors. Cell analysis methods such as flow cytometry and fluorescence microscopy will be used. The project will also include recombinant protein expression and purification of proteins and antibodies from plasma. An important aim of the project will be to establish a cell-based screening model for complement and coagulation activation on the endothelial cell surface. As a postdoctoral fellow you will also be expected to assist in the supervision of master students and doctoral students.

In this project, the selected candidate will join us in conducting research in machine learning and system identification research, developing data-driven methods to learn signals and systems from data. There will be a focus on developing robust methods with mathematical guarantees, focusing on stability, statistical and optimization considerations. We will work in applications to cardiology and electrophysiology. The exact details of the research project are decided in a dialogue between the postdoctoral researcher and the supervisor.

We are looking for a postdoctoral researcher in Computational Biology, Bioinformatics or Data Science. The research group is connected to SciLifeLab and is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation. The candidate will work in the lab of Marcel Tarbier (https://www.scilifelab.se/researchers/marcel-tarbier/). Our research is focused on computational method development (statistical approaches and machine learning) for single-cell gene expression data (such as single-cell RNA-sequencing, spatial transcriptomics and in situ sequencing) to infer complex cell features. The two main projects the candidate will work in aim to infer cellular lineage relationships and cellular micro-environments respectively. This is achieved through a data-driven approach, where large complex datasets are quantitatively dissected and subtle signatures are linked to additional observations. This in turn lays the basis for applications in precision medicine related to human biopsies and cancer heterogeneity. The candidate will have the opportunity to individually drive the project forward and develop their own line of research as well as to extent their skills at the intersection of mathematics, programming and biology.

Branch prediction is increasing in importance as processors have more in-flight instructions. Our hypothesis is that we can produce fundamentally better predictions by merging different prediction contexts rather than competing between different predictor outcomes. The reason to believe in this hypothesis is that the different contexts used by different predictors today are not independent: for example, loops and statistically predicted branches are intermixed and affect each other. Combining contextual information before finding patterns is fundamentally different from combining the final predictions after each predictor finds its own context-specific pattern. If we can combine different types of contextual information (e.g., loops and statistical counts and histories), we believe we can create a more sophisticated “meta-context” that allows us to recognize patterns from the combined context information, leading to better predictions. The flip side is that it may be correspondingly harder to recognize the right patterns, particularly at runtime. This project contains two parts: looking at the underlying potential by studying application behavior and looking at the tradeoffs to make a practical design. 

The combination of probabilistic models and deep learning remains highly interesting. In this project we will develop and explore models of this kind for dynamic phenomena with the use of temporal data. These dynamical models are essential in explaining and understanding the world around us since many phenomena evolve over time. When it comes to modeling nonlinear dynamics, flexible models have the potential to significantly enhance performance over simple ones. Related to this is the task of deriving algorithms that can be used to learn the unknown model parameters from the measured data. In this project, the successful candidate will conduct basic research and methods development, but if there is interest also engage in some of the collaborations we have within medicine or biodiversity via our established collaborators in cardiology, neuro surgery and biology. Technical keywords for the position include: probabilistic models, deep learning, nonlinear dynamical/temporal models and Bayesian inference.

The successful candidate will perform high-quality research. They will also develop the Center by acting as a link between the groups and being involved in activities, such as kick-off meetings and seminar series, together with the research coordinator of the center. The candidate will use high-end methodologies and instrumentation and work collaboratively with the goal to pinpoint the chemical mechanisms of life. As a postdoctoral researcher, they will collaborate with PhD students, students, and researchers in the groups and the center in an interdisciplinary setting, in addition to writing publications and grant applications. They will also be involved in outreach activities.

Additive manufacturing (AM), or 3D-printing, has enabled not only a complete freedom-of-design of components, but also the development of alloys with new compositions and with tailored microstructures, potentially allowing for lower material and fuel usage in the case of light-weight alloys, and corrosion rates that are more adequate for use in temporary implants. However, process parameter development for AM is complex, time-consuming and very costly, including high amounts of material and energy waste, and even more so for particularly challenging alloys such as Mg-based ones, which require substantial research efforts. In this project we will develop machine learning models to i) enhance the efficiency of the process development, as well as to ii) develop a better understanding between process parameters and the resulting microstructure, as applied to Mg-based alloys. These alloys are promising for applications in the aerospace and transport industry, as well as biomaterials. The project focus will be on developing machine learning methods for AM that capture physical principles, for instance, through simulations.

Are you interested in working with energy transitions, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University.

The Department of Earth Sciences conducts research and education in a wide range of areas, from the origins of life on Earth, critical and rare metals and minerals, rock formation, landslides and volcanoes, weather and climate, water resources, natural disasters, to energy resources and sustainable development. We are one of the most inclusive departments of Earth sciences in all of Europe and our education and research are conducted in both Uppsala and in Visby.

The postdoc will join the Digital Ecologies Lab, and be a key staff member in a new research project entitled “EV drivers in the driver’s seat – smart charging from a user perspective”, funded by the Swedish Energy Agency.  The project is led by Bartusch, with many co-investigators including Hazas, and Sara Renström at Research Institutes of Sweden (RISE).  Partners include Uppsala Parkering and Charge Node.  The purpose of the project is to develop and test communication and control technology as well as combined parking and charging tariffs and a related mobile app for public smart charging and V2G. Development and pilot tests are carried out in a laboratory and on a charging station at Uppsala University. The subsequent field tests are carried out at a mobility house with smart charging points, solar cells and energy storage. As part of the development process, the aim is also to increase knowledge about economic, social-psychological and legal factors that influence EV drivers’ inclination and opportunity to engage in smart charging and V2G.

Are you interested in working with soft materials, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a Postdoctoral position at Uppsala University jointly with the European Spallation Source.

Do you want to work with research, supported by competent and friendly colleagues in an international environment? Are you looking for an employer committed to sustainable employment practices and offering secure and favorable working conditions? Welcome to apply for a position as a Postdoctoral Researcher at the Department of Pharmaceutical Biosciences at Uppsala University.

The European project SmartPV aims at merging photovoltaic and smart windows approaches in innovative energy and resource-efficient glazing. Uppsala University coordinates the project and develops novel chromogenic coatings. Specifically, thermochromic and photochromic thin films (vanadium oxide and lanthanide oxyhydride-based) grown by sputter deposition on glass and polymeric substrates are targeted.

Material characterization of films will primarily be done by X-ray diffraction, electron microscopy, spectrophotometry, photoelectron spectroscopy, FTIR, Raman, and electrical transport measurements. In addition, the project involves data analysis, data simulations, writing reports (scientific articles and project documents), and oral presentations at European project meetings and conferences.

The successful candidate for this Postdoctoral student position will have opportunity to study a variety of energy and electrocatalytic materials using operando x-ray-based methodology, and complementary techniques.

Within the position, you also have the opportunity to learn how to design materials using different methods and to characterize electrocatalytic properties. The candidate will be part of a collaborating research group that share the same general goal of unravelling the functionality in such interesting and challenging energy materials and also develop their performance.

We are engaged in the field of computational materials science, with a focus on magnetic materials for energy applications. Our current project concentrates on developing sustainable permanent magnets for green energy applications. The project is a collaboration between geologists, chemists, and physicists granted by the Swedish Research Council (VR). The task of our computational group is to predict the intrinsic properties of magnetic materials using natural rare-earths compositions from ores discovered in Swedish bedrock. The candidate will combine work with DFT codes, many-electron phenomena and spin dynamics methods. The key properties of our studies are magnetization, exchange interations, and magnetocrystalline anisotropy. Working on the interdisciplinary VR project offers a unique opportunity to be part of a diverse research team that spans materials modelling and experimental work. 

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: 2 Postdoctoral positions in hydrothermal processes in volcanic systems

Deadline : 17 April 2025

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Are you interested in working with stochastic control theory, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University.

The Department of Mathematics conducts research and provides education at undergraduate to graduate level in mathematics, applied mathematics and statistics. The number of employees is 120, including 30 PhD students. The Department has three research programs: analysis and probability, algebra and geometry, applied mathematics and statistics.

Are you interested in working with innovative exploration methods, with the support of competent and friendly colleagues in an international environment? We welcome you to apply for a postdoctoral position at Uppsala University.

The postdoc will conduct research within the newly established Smart Exploration Research Centre. A major component of the research involves developing seismic solutions with cutting-edge distributed-acoustic sensing or DAS methods for both deep targeting and site characterization including mine tailings. The postdoctoral fellow will also work within a larger research team including experts from different universities and industry partners. The postdoc will be responsible to promote project activities through high-quality publications. It is also possible to be part of a series of geophysical prototype testing and validation work. The project includes fieldworks, and the candidate should be willing to spend time in the field collecting data.

Den sökande kommer att karakterisera proteinkomplex med hjälp av lipid-vesiklar. Det gäller båda membranproteiner samt lösliga proteiner som har instängts i vesiklar. Med hjälp av olika molekylärbiologiska och biofysiska tekniker, framför allt massspektrometri och kryo-elektronmikroskopi, kommer vi belysa proteinernas struktur och interaktioner och hur de påverkas av lipiderna. Fokus för det postdoktorala projektet är att fortsätta det pågående arbetet i gruppen kring massspektrometriska metoder för att studera proteiner under så livsnära förhållanden som möjligt. Den postdoktorala forskaren kommer att uttrycka och rena fram proteiner, följa deras struktur och interaktioner i vesiklar med masspektrometri och kryo-elektronmikroskopi, och korrelera strukturförändringar med biologisk aktivitet. Projektet är ett samarbete med Sebastian Eustermanns och Thomas Quails grupper på EMBL i Heidelberg.