07 Postdoctoral Fellowship at University of Bergen, Bergen, Norway

The project is related to digital medicine and artificial intelligence, particularly the goal of developing a digital twin for the body’s hormonal system (the endocrine system). This involves creating a dynamic, interactive real-time data model that represents the endocrine physiology at an individual level (precision medicine), both in healthy and sick individuals. A digital twin is built up of multimodal data from a variety of sources, for instance sensor data (for instance from watches and phones), self-reported patient data, and omics data from tissue analyses (genomics, transcriptomics, proteomics, etc.). When such data are compiled for an individual, one may be able to develop therapeutic tools that predict individual response to various treatments and establish new diagnostic tools. The research group has access to clinical expertise, patient material, and tissue samples, and to expertise on organoid stem cell-based models as a basis for omics data, but needs to strengthen its analytical competence. Work tasks that are anticipated include:

• Implementation of a secure clinical data storage platform.
• Development of analysis tools for multimodal data including real-time data streams as well as omics data.
• Contribute to the development of a digital endocrine twin.

The research group has collaborations with, for example, Stanford Medical, and there will be possibilities for international mobility.

In all living organisms, there is a subset of small coenzyme molecules that participate in thousands of biochemical reactions, thereby enabling and coordinating metabolism. In the course of evolution, the same molecules have attained more and more key roles as regulators of virtually all biological processes, often through posttranslational protein modifications. This is illustrated, for example, by the use of NAD in a multitude of metabolic reactions and at the same time as substrate for ADP-ribosylation and protein deacetylation. HubMOL aims to unravel the mechanistic principles of how these molecules of life interact to enable and control both metabolism and signaling. The project combines world-leading competences in synthetic and analytical chemistry, biochemistry, molecular genetics, bioinformatics and advanced technology development. Through their direct association with established medical research centers (NeuroSysMed with a focus on neurodegeneration, KG Jebsen Center on Parkinson’s Disease), the core scientists will closely collaborate with clinicians to apply the findings from basic research to disease diagnostics and treatment.

HubMOL is an interdisciplinary, international project with partners in Norway, Austria and the USA. The successful candidate will work in the group of the project leader, Prof. Mathias Ziegler, at the Department of Biomedicine, who is leading studies on metabolism and signaling, closely collaborating with Prof. Ines Heiland, who is an expert in metabolic modeling. Active participation in and contribution to joint project meetings and workshops is expected.

The successful candidate is expected to lead this sub-project with diligence and a high level of independence, initiative and problem-solving capacity. The position will require being constantly updated with methodological developments and advances in the field. At the same time, this position will offer substantial opportunities for career development and growth. The candidate will work with state-of-the-art analytical instrumentation, generate extensive experimental data sets and analyze them using advanced bioinformatics methods.

The PhD project has work title Wideband Methods for Complex Acoustic Waveguides. The work will be carried out with main supervisor at University of Bergen in planned collaboration with external partners. This is an excellent opportunity to work with ultrasound acoustics and signal analysis in the scientific forefront, in short distance to industrial applications.

Several acoustic methods are used for non-destructive evaluation (NDE) and structural health monitoring (SHM) of mechanical constructions. One family of such methods monitor the integrity of bar-, plate-, and pipe-like elastic structures by means of guided ultrasonic waves (GUW). Transmitting ultrasound transducers excite GUW propagation modes in the structure. Receiving transducers are used to detect changes in scattering, signal amplitudes, or phase (travel time). Such signal changes carry information about events and processes such as, e.g., crack formation, dimensional changes, delamination, marine growth, scale and wax formation, corrosion, and erosion.

The PhD project will review the current scientific state of the art of relevant wideband signal analysis methods. This will be a starting point for studying methods for NDE and SHM on real-world mechanical structures. Analytical, numerical, and experimental methods will be combined in the study. Application cases found in the SFI Smart Ocean centre consortium will receive particular attention as ultimate technological goals following the PhD work.

Shaping European Research Leaders for Marine Sustainability (SEAS) is a postdoctoral research fellowship programme for 37 fellows launched and managed by the University of Bergen (UiB). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101034309.

In this fifth call, open April 29 – June 10 2024, we invite talented experienced researchers to apply for one fellowship at the Faculty of Law.  The successful candidate will be employed in a fixed-term fulltime postdoctoral research fellow position at UiB.

There is a vacancy for a predoctoral fellow at the Centre for Research on Discretion and Paternalism (DIPA) at the Department of Government, University of Bergen, Norway. The position is for a fixed-term period of 4 months. The formal name of the predoctoral position in the university system is “research assistant”. Total employment as a predoctoral fellow in this category of positions (research assistant positions) cannot exceed two years.

A predoctoral fellow is a recruitment position where the main task is to be a supporting entity to academic staff in their instructional and research endeavors. A predoctoral position is for candidates that seek a career in academia and aim for a PhD. The position will provide the opportunity to gain insight into scientific work and methodology by working for an experienced PI and to be a team member in an ambitious research team of young researchers. The candidate´s work task will be related to collected survey data and the research projects at the DIPACentre, University of Bergen, Norway, in collaboration with PI for the projects Professor Marit Skivenes. Working place will be Christes gt. 15, Bergen.

• The overall goal of the project is to characterize and understand key elements of the pathomechanism of ME/CFS through high-dimensional data from patients and experimental laboratory approaches. The project aims to contribute to the discovery of effective biomarkers and therapy for these patients.

• The candidate will work with state-of-the-art technologies (e.g. -omics, flow cytometry, and others) and related bioinformatics workflows. The candidate will analyze patient samples, as well as utilize in vitro and cell models to address different aspects of the targeted hypothesis.

• Focus areas include mechanisms leading to impaired microcirculation, and possible roles of vascular cells, tissue hypoxia and immune dysregulation, including neutrophil changes.