08 Postdoctoral Fellowship at Umea University, Sweden 

The research project is funded by the Swedish Research Council (VR) and serves to develop novel graph-based methods for semantic parsing of multimodal data. In other words, the translation of composite media items such as a video with audio tracks and subtitles, or a digital news article with text and images, into structured representations that capture central aspects of the combined media. The problem appears in many technological areas. In robotics, it takes the form of language grounding, where the linguistic constituents of a natural language command are linked to real-world objects, attributes, and relations. In media asset management, it appears as automatic captioning of images. It is also of inherent value in machine learning, because it allows us to transfer knowledge between different modalities. Knowledge that we have learnt from text can, e.g., be used to understand images.

Our research group works interdisciplinary from preclinical to clinical studies, “bench-to-bedside”, within the Wallenberg Center for Molecular Medicine (WCMM). Our goal is to find good biomarkers for individualized treatment through characterization of cells from tissue and blood. And find treatable mechanisms for metastatic prostate cancer. By isolating circulating tumour cells (CTC), immune cells, exosomes and cell-free DNA from the blood, we study metastasis in prostate cancer. By characterizing CTCs with RNA and DNA sequencing at the single cell level, we want to identify the CTC heterogeneity in patients with metastatic disease and study early treatment response.

This postdoctoral position is part of a Swedish council financed research project to unravel the regulation of programmed cell death at the molecular level with focus on the structure of the proteins and biological membranes involved in this important process. Important key players in the mitochondrial (intrinsic) cell death pathway are membrane-active proteins of the Bcl-2 family. The main objective of this project is to understand the function – and underlying structural properties – of these proteins and their interactions with the mitochondrial membrane environment. For this purpose we will use structural biological methods focusing on solid-state NMR spectroscopy of lipid-protein complexes, complemented by liquid-state NMR. In addition, we will also use neutron reflectometry on these lipid protein complexes). You will primarily study the membrane bound Bcl-2 proteins and their mutual interactions.  In addition, you will also be supporting NMR based work on human protein kinases which can be involved in human cancer, in part, through their regulation of Bcl-2 proteins.

You will be part of a team studying processes for the formation of methylmercury in oxygen deficient coastal environments with a focus on how microbial community composition, chemical speciation of mercury and molecular composition of organic matter control this process.

Mercury accumulates in aquatic biota as neurotoxic methylmercury and is of concern for global public health. Oxygen deficiency is spreading in coastal seas and the global ocean which could increase methylmercury formation by anaerobic microorganisms and thereby increase methylmercury exposure to marine food webs. Our understanding of the mechanisms and drivers for methylmercury formation under such scenarios is however insufficient, hindering quantitative predictions and risk management.

Advancements in artificial intelligence (AI) have the possibility to significantly contribute to improve patient treatments, in a trend towards personalized and predictive medicine. Indeed, while deep learning has shown its potential in many fields, healthcare included, we have assisted to extensive research of new quantitative biomarkers computed from the medical data already collected in clinical practice. However, most of the AI models consider only unimodal data, while there is the need to investigate the fusion between the heterogenous nature of healthcare data, such as images, molecular biomarkers, clinical data, and electronic health records (EHRs). Within this project, we are interested in studying multimodal deep learning as well as in explaining the decisions taken by this paradigm, two areas of great interest at its infancy. In particular, in multimodal deep learning we aim to address open scientific questions, i.e., which modalities are useful, how to fuse them and where this integration should happen, how to embed in the training any process able to learn more powerful data representations, how to get the optimal fusion architecture robust to missing data and missing modalities. As for multimodal explanations, there is the need to help physicians, regulators, and patients to trust AI models. However, the few efforts in multimodal explanations available in the literature have been directed towards computer vision and natural language applications, so that multimodal explanations are completely missing in healthcare. This project therefore addresses this challenge, particularly focusing on pre-modeling, during modelling and post-hoc modeling explanations at local level.

We are looking for a post-doctoral researcher in marine microbiology that will investigate prokaryotic maintenance metabolism at Arctic conditions. Applied methods include electron microscopy, omics, respiration measurements, statistical analysis of data and authorship of scientific articles. It is a full-time position limited to 2 years. Start date is January 1st, 2023. 

Inflammation of the gums (gingivitis) is very common and is caused by bacteria found in connection with the teeth and gums. Due to factors that are not fully understood, only some develop periodontitis, which means that the gingivitis process turns into an extensive destruction of the collagen-rich connective tissue and bone that constitute the attachment of the teeth. Bone loss is not only seen in periodontitis, but also in, for example, peri-implantitis and rheumatoid arthritis. In these diseases, bone loss is considered an irreversible condition that risks impairing the function of teeth, implants and joints. However, the molecular mechanisms behind inflammatory bone loss are not fully mapped. Our hypothesis is that there are common molecules that cause inflammation-driven bone loss in individuals who, due to genetic factors, are more susceptible to disease. The overall aim of the project is to identify markers to detect who is at risk of suffering from inflammatory bone loss, such as periodontitis, before the bone breakdown begins. With our research, we also want to discover new osteoimmunological principles that could be attacked with targeted therapy to slow down or prevent inflammation-driven bone loss.

As a post doctor in technology or engineering education, you will be part of the Umeå Science Education Research (UmSER) environment. Research topics explored in UmSER include environmental and sustainability education, the role of emotions in science and technology, and identity and power in teaching and learning.

As a post doctor in educational science, you will be part of the career program for young researchers run by Umeå School of Education. The position is in technology or engineering education, but also aims to strengthen educational research at Umeå University. As a post doctor in the career program, you will therefore be part of a broader interdisciplinary environment in addition to your main research context in technology or engineering education.