Postdoctoral Fellowship (14) at Stockholm University, Sweden

The Canadian Beaufort Sea shelf is an ideal region to look for the effect of sea level rise, and large freshwater input on Holocene primary productivity, sea-ice cover and ocean acidification. In parallel, the shallow lakes of the Mackenzie region in the Northwestern Territories (Canada) are at the forefront of recent climatic disturbances, with rising winter air temperatures, change of the timing of the spring freshet and decreased precipitation. Scientific questions can also relate to shifting methane dynamics in a changing Arctic.

We seek outstanding postdoctoral researchers, with background in computational, theoretical and/or observational projects, to develop and deploy cutting-edge machine-learning and AI methods for astrophysics and cosmology, enabling precision tests of fundamental physics with current and next-generation galaxy and time-domain surveys. You will work closely with our teams on the Rubin Observatory ‘s LSST, Euclid, ZTF, and LS4.

Complexity is a fundamental concept that quantifies the difficulty of accomplishing a particular task, given a specific set of allowed, simple operations and a procedure to achieve it. As such, it is an important part of many fields from mathematics to computer science. Surprisingly, physics still lacks a precise definition of quantum complexity and providing it is one of the most urgent problems at the cutting-edge of quantum theory and quantum gravity.

The position within the ERC Consolidator project “Quantum Complexity from Quantum Field Theories to Quantum Gravity” (PI: Pawel Caputa) will aim to fill this gap.

The goal of the project is to develop universal measures of quantum complexity for many-body systems, quantum field theories and quantum gravity. The milestones of the project include: synthesizing and developing physical measures of complexity, formulating them in exact holographic models, and applying them to shed new light on the physics behind black hole horizons and spacetime singularities.

The candidate will work on problems at the intersection of mathematical statistics, machine learning, and generative modeling, particularly for sequential data arising in complex dynamical systems. The candidate is expected to carry out research and publish their findings in top conferences and journals, and help in the management of the group, as well as supervision of students on research projects. The position is meant to further the careers of early-career researchers who wish to pursue a career in academia. The job description may be changed during the contract period or upon contract renewal.

This position is part of the Wallenberg Initiative on Networks and Quantum Information (WINQ), supported by the Knut and Alice Wallenberg foundation (KAW).

The Postdoctoral Fellow position is associated with the ERC-StG project CIRCULIG “Circular lignin materials from well-defined functional building blocks”.

The Postdoctoral Fellow will focus on lignin electrochemistry, including the functionalization of lignins and their derivatives, as well as the use of lignin nanomaterials as supports and active components in catalytic, organic, bio-, and electrochemical reactions. Lignin-based catalyst carriers, electrodes, and other functional materials will be characterized using state-of-the-art analytical techniques. A particular emphasis will be placed on circularity, including reusability and the potential for safe upcycling and recycling. The Fellow will work within an interdisciplinary team with deep expertise in lignin spanning molecular, supramolecular, and macroscopic scales.

The position is based in the Sustainable Materials Chemistry (SUSMATCHEM) research group, which develops materials from industrial side-streams, with a particular focus on lignin. The group consists of about 25 members with diverse expertise in chemistry and engineering. The Postdoctoral Fellow will work in this interdisciplinary environment and carry out bottom-up research on hybrid living materials, contributing to the broader goal of replacing fossil-based materials and advancing sustainable solutions.

We are offering a Postdoctoral Fellow position within the LIGNOLOOP project, funded by the Knut and Alice Wallenberg Foundation. This part of the project focuses on developing innovative textile coating systems based on lignin nanoparticles. The Postdoctoral Fellow will be responsible for developing methods to stabilize lignin nanoparticles under conditions relevant to textile applications. These methods may include, but are not limited to, physical stabilization and atom-efficient click reactions. In collaboration with project partners, we also aim to establish structure–property–function relationships.

The position is based in the Sustainable Materials Chemistry (SUSMATCHEM) research group, which develops materials from industrial side-streams, with a particular focus on lignin. The group consists of about 25 members with diverse expertise in chemistry and engineering. The Postdoctoral Fellow will work in this interdisciplinary environment and carry out bottom-up research on hybrid living materials, contributing to the broader goal of replacing fossil-based materials and advancing sustainable solutions.

The position will be associated with the project “Observational constraints on Arctic Ocean methane systems as tipping elements and triggers of climate overshoot”, funded by the Knut and Alice Wallenberg (KAW) Foundation. The project targets methane releases from thawing subsea permafrost and collapsing hydrates of the Arctic Ocean. High methane concentrations have been documented on the Eurasian Arctic Ocean shelves and slopes, yet the sources, release processes, degradation and emissions to the atmosphere, and future trajectories are highly uncertain. The project aims to answer these questions by integrating observational and modelling tools. This post doc position will be associated with the research group of Örjan Gustafsson and will be part of a larger international research team working on Arctic Ocean subsea permafrost, hydrates and methane, including Stockholm University partner groups of Birgit Wild, WeiLi Hong and Christian Stranne.

The successful candidate will conduct research that focuses on developing an open-access, interactive Regime Shift Explorer to map the risk of regime shifts across the world’s ecosystems.

You will:

• Combine existing understanding of regime shifts as captured in the Regime Shift Database with global social and ecological spatial data.
• Contribute to the design and implementation of the interactive web platform, ensuring it provides clear and actionable information on regime shift risks and strategies to build resilience.
• Collaborate closely with SRC researchers and NatCap to link the Regime Shift Explorer to financial decision contexts, such as screening investments for regime shift risks.
• Publish results in leading academic journals and engage with partners and stakeholders to promote the tool’s use for research, policy, and investment.

This position will be based at the Stockholm Resilience Centre, Stockholm University, with research visits to Stanford’s Natural Capital Project expected. You will work under the supervision of Prof. Garry D. Peterson (SRC), Dr. Megan Meacham (SRC), Dr. Juan Rocha (SRC), and Dr. Tong Wu (Stanford) who have extensive experience with regime shifts, ecosystem services, and connecting ecology and finance. 

Artificial Intelligence (AI) is a rapidly growing research field that draw on technologies such as machine learning, statistics, and decision support. In recent years, developments in deep learning and reinforcement learning have resulted in high-performing models and tools for complex applications. At the same time, the concept of the digital twin has become central throughout the system development lifecycle – from design and planning to operation, monitoring, and optimization of product and services. A data-driven digital twin can be described as a digital representation of a physical system or service, continuously updated by live data streams to enable monitoring, time series forecasting, explainability, and decision-making. This postdoctoral project aims to combine artificial intelligence and machine learning methods, with a particular focus on time series forecasting and explainable machine learning, together with the conceptual architecture and prototypes of digital twins. The main objective is to develop methods that can support the healthcare sector, for example through prediction of patient trajectories, resource needs, and real-time clinical decision support. As a complement, the methods may also be applied to smart buildings, where digital twins can be used for energy optimization and improved indoor environments. The project will make use of real-world, streaming data from these domains to ensure both scientific impact and practical relevance.

We are looking for a biochemist with MD simulation experience on membrane proteins, particularly membrane transporter proteins. The work includes planning and running research projects, which aim to determine the structure and function of secondary solute protein carriers and their dynamics. Supervision of doctoral students and other participants in the project is also required. Experience of working with membrane transport proteins; production, isolation, functional studies and MD simulations are requirements.

The candidate is expected to propose an independent research project, demonstrating both the autonomy expected from a postdoc and potential for fruitful collaborations with members of the group. Other tasks may involve helping with the management of the group, as well as co-supervision of students on research projects. The job description may be changed during the contract period or upon contract renewal.

There are no teaching requirements for this position, but for candidates interested in teaching, Nordita has connections with nearby institutions where it is sometimes possible to arrange teaching opportunities (Stockholm University, KTH, and Uppsala University). The position is meant to further the careers of early-career researchers who wish to pursue a career in academia.

This position is part of the Wallenberg Initiative on Networks and Quantum Information (WINQ), supported by the Knut and Alice Wallenberg foundation (KAW). It is aimed at nurturing and bringing together expertise from both quantum information science and complex dynamical systems to address major open challenges in these fields. WINQ is located within the conducive research environment of Nordita. Successful candidates for a position in WINQ may also have an opportunity to collaborate with other KAW initiatives across Sweden in the fields of artificial intelligence (WASP) and quantum technology (WACQT).

The Atmospheric group at MISU conducts research with a focus on physical, chemical and dynamical processes in the Earth’s mesosphere and lower thermosphere. This is strongly based on the Swedish satellite missions Odin and MATS as well as sounding rocket experiments. We are looking for a postdoctoral fellow who will be an integral part of the research group and connect data from these projects to numerical model studies. The Odin mission has provided 25 years of data on noctilucent clouds and related atmospheric properties, which can serve as a basis for studies of solar and dynamical effects on the atmosphere. MATS extends mesospheric studies to smaller spatial scales by employing tomographic analysis of airglow emissions and noctilucent clouds. Sounding rockets are used in particular to address photochemical processes connected to airglow emissions.