07 Postdoctoral Fellowship at Stockholm University, Sweden

The Department of Physics offers a postdoc position available for a highly motivated and enthusiastic candidate for studies in the area of biomolecular physics. The applicant is expected to play a key role in exploring the physics of biomolecular condensates which are linked to the emergence of life by concentrating key chemicals that facilitated the formation of the earliest stable cells. This is a highly interdisciplinary project in the crossroads of biophysics, data science and physical chemistry.

The current project aims to development of advanced microdroplet reactor setups which offer precise control over biomolecular condensation and are designed for experiments at large-scale facilities, such as X-ray storage rings and X-ray free electron lasers (XFELs).

This project is connected to the group endeavour to increase the sustainability of organic bioelectronic materials and devices. The Postdoctoral Fellow will play a central role in the Team, by developing new materials, processes, and/or device configurations that provide the performance needed for applications and sustainable design. The new materials and concepts will have direct application within the bioelectronic devices developed in the group. Advanced characterization techniques will be used to understand their structure-property relationship of materials and the impact of fabrication on device performance.

This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability (WISE, wise-materials.org). WISE, funded by the Knut and Alice Wallenberg Foundation, is the largest-ever investment in materials science in Sweden and will encompass major efforts at Sweden’s foremost universities over the course of 10 years. The vision is a sustainable future through materials science. Read more: https://wise-materials.org.

All early-stage researchers recruited into the WISE program will be a part of the WISE Graduate School (https://wise-materials.org/research/graduate-school/), an ambitious nationwide program of seminars, courses, research visits, and other activities to promote a strong multi-disciplinary and international network between PhD students, postdocs, researchers, and industry

The position will be associated with the Wallenberg (DDLS-WASP) project Machine-Learning how our Cells Capture Energy – Data-Driven Studies of Membrane Protein Function, Evolution, and Disease. We are searching for a highly motivated postdoc to join our collaborative project on multiscale simulations & machine-learning (ML) applied to membrane protein function. The candidate will work in the Lab of Prof. Ville Kaila (Stockholm), with collaboration and research exchange with the Dr. Simon Olsson Lab (Chalmers). The project combines ML approaches with computational, biochemical, biophysical, and structural data, with aims to provide a basis for understanding how proteins power the energy metabolism of our cells, the evolution that led to the emergence of these intricate biological complexes, and how disease related mutations alter the protein function.

The post-doctoral position will be located in the research group of Assoc. Prof. Kruve and associated with the ERC project ” Machine Learning and Mass Spectrometry for Structural Elucidation of Novel Toxic Chemicals”. The project aims to develop novel machine learning approaches for identification, quanitifcation and toxicity assesment in non-targeted LC/HRMS screening.

This project aims to generate the structures of novel chemicals detected with non-targeted screening with liquid chromatography high resolution mass spectrometry (LC/HRMS) that are yet lacking in the spectral and structural libraries. The project aims to develop a workflow to assemble the chemical structure of the detected chemicals based on the molecular formula as well as other empirical analytical information, such as fragmentation spectra, retention time, and collision cross-sections. For this purpose, different graph-based generative AI models such as graph generative adversarial networks, flow-based models and diffusion models are of interest.

The position is associated with the project Genome evolution in parasitic plants and the current focus is on largest clade of parasitic plants, the order Santalales. Within the Santalales, the mitochondrial respiratory pathways has experienced unique changes compared to all other land plants and the mitochondrial genome can be strongly modified. In a phylogenetic framework the current project aims at tracing this extraordinary mitochondrial genome evolution and its potential correlation with traits related to the diverse parasitic lifestyles within the Santalales.