Postdoctoral Fellowship (23) at ETH Zurich, Switzerland

Organic redox flow batteries are a promising next-generation technology for large-scale, safe, and sustainable energy storage. Their performance relies critically on the ability to store electrons in robust, cost-effective, and highly soluble redox-active organic electrolyte molecules.

Our project aims to advance this field by developing new synthetic approaches to functional organic compounds suitable for use as electrolytes in flow battery systems. The overarching goal is to expand the accessible chemical space and identify structures with improved stability, performance, and scalability.

At ETH Zurich, this work is embedded in an interdisciplinary research environment spanning organic and inorganic synthesis, electrochemistry, and materials science, with the added dimension of collaboration with an industrial partner who will evaluate materials in device-relevant conditions.

The following project, where ETH Zurich plays a crucial role, significantly contributing to various research and development aspects of nuclear safely. The focus of the project is to gather essential data on the liquid source term, improve our understanding of the associated phenomena and develop tools to simulate the relevant processes. In collaboration with PSI, ETH reviews data from previous projects, focusing on leaching tests of Chornobyl’s lava in various liquids, and also contributes to reviewing data from Fukushima-related research projects, with a particular focus on thermodynamic data for caesium and strontium compounds.

ETH is also actively engaged in developing and validating new simulation models. This includes reviewing other simulation tools and databases, such as thermodynamic solvers, to enhance our understanding of liquid speciation and dissolution process. ETH contributes to summarizing knowledge on the use of the GEMS thermochemical solver and HERACLES thermodynamic database, specifically dedicated to nuclear applications. These efforts are integral to developing and integrating new models into severe accident (SA) codes, which include assessing and validating thermodynamic data to predict the behaviour of fission products like caesium and strontium in liquid phases during accidents.

Position in the NorSCAPE Project: “Norway Spruce in a Changing Climate: Adaptation, Acclimation, and Physiological Responses for Resilient Forests in Europe” for 2 years, with possibility of extension. This project is in collaboration with the COSTAction CLEANFOREST.

Norway spruce (Picea abies) is a cornerstone of Europe’s forests and forestry sector, facing increasing challenges from climate change. This position offers the exciting opportunity to join the NorSCAPE project, which aims to disentangle the physiological mechanisms underpinning resilience and vulnerability across its distribution range. In collaboration with international partners and the ETH team, your role in this project will involve research on the adaptation and acclimation potential of spruce, using tree-ring analysis, stable isotope measurements across forests and provenance trials, to inform forest management and policy under global change. This project will be carried out in close collaboration with the WSL and the Stable Isotope Research Laboratory in Birmensdorf.

The Robotic Materials group is looking for three postdocs and one PhD for the project funded by ERC Starting Grant: “Distributed Addressable Robotic Material via Wavelength-Division-Multiplexing (ColorfulAct)”. ColorfulAct aims to establish the building blocks of physical intelligence parallel to nodes and connections to artifical intelligence. We will develop distributed and addressable robotic actuating materials that demostrate multifunctionality through the broad bandwidth of light.

The Robotic Materials group headed by Prof. Hedan Bai at Department of Materials was established in October 2023. We are an international and interdisciplinary team of material scientists, roboticists, engineers and chemists with a passion for futuristic robotics. We take a bottom-up approach to robotics and develop soft materials and devices that would enable unusual form and unconventional functions for broader robotic applications.

At the Professorship of Solid Mechanics (SMEC) in the Institute for Building Materials at ETH Zurich, we aim to understand how materials deform, degrade, break, and ultimately fail. Our research is driven by curiosity about the physical mechanisms that underlie failure and by the ambition to translate this understanding into more reliable and resilient materials and structures. By combining numerical modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools for mechanical failure.

Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science, mechanics, and applied physics. We work across a broad range of topics, including the mechanics of particle systems (colloidal and granular), architected and topologically interlocked materials, the mechanics of fragility in collagen, the mechanics of earthquakes, fracture of soft materials, and modeling failure in multiphysical processes such as corrosion-driven degradation of concrete. What unites these efforts is a shared curiosity about why complex materials fail and a commitment to developing new concepts, experiments, and models that advance our understanding of failure mechanics.

We are looking for candidates with one of the two profiles below, aligned with our lab’s main research branches.

1. Mathematical foundations of trustworthy ML – working on topics such as:

• (Robust) distributional generalization, transfer learning, causality
• Multi-objective settings and alignment, RL theory
• Statistical learning theory, optimization (e.g., implicit bias)
• Robustness (broadly defined), privacy, memorization, unlearning, interpretability
• Grounding AI/ML concepts in the social sciences (philosophy, psychology, law)

2. Real-world impact – working on topics including (but not limited to):

• Real-world problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy, or interpretability are relevant
• LLM adaptive evaluation and post-training, with clean mathematical proofs for proof-of-concept

The candidate is expected to work on the broad theme of reinforcement learning (RL), such as (but not limited to) 

• Theory of online learning, reinforcement learning, and data-driven control 
• Learning in games, and multi-agent RL 
• RLHF and alignment in LLMs
• Representation learning in RL
• Transfer learning in multi-task bandits and RL
• Statistical or generative decision making

The exact project scope will be tailored to the candidate’s strength and expertise. The candidate is expected to collaborate closely with the research supervisor and the ODI team members, and assist in mentoring Master’s or Bachelor’s thesis projects. 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoctoral Researcher / Senior Scientist

Deadline : Open Until Filled

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Design++ is the Center for Augmented Computational Design in Architecture, Engineering and Construction (AEC) at ETH Zurich. The center’s vision is to remove collaboration barriers in AEC and urban & landscape planning to address pressing sustainability challenges, boost productivity and simultaneously deliver high quality spaces. This is achieved through innovation in computational methods, artificial intelligence (AI), and extended reality (XR). Design++ fosters cross-departmental research, education, and industry collaboration to drive transformative change in the built environment.

The Postdoctoral Fellowship Program, made possible via our Strategic Partnership with Halter Group AG, funds a two-year postdoc position annually over 5 years. The goal is to advance computational methods and AI/XR for Architecture, Engineering & Construction (AEC) and urban/landscape planning – bridging research to practice and expanding the potential for impact. As a fellow, you will be co-mentored by two ETH professors from two different departments. If you don’t have hosts yet, Design++ can help match you based on your proposal.

The affiliated research groups of the center offer a broad spectrum of research topics in robotics, including but not limited to:

• Soft and Musculoskeletal Robotics: Designing and fabricating bioinspired robots using compliant materials for adaptable and safe interactions in an unstructured world.
• Robotic Locomotion and Manipulation: Creating innovative solutions for legged robots and robotic manipulators to enhance mobility and interaction in complex terrains.
• Biohybrid Robots: Creating robots from living cells, tissues, and synthetic materials that are powered by chemical energy and can interact with and reason about the world.
• Perception and Computer Vision: Advancing techniques in 3D modeling, object recognition, and environment perception to improve robotic sensing capabilities.
• Human-Robot Interaction: Investigating sensory-motor actions and interactions between humans and machines to enable or enhance supportive or cooperative tasks.
• Computational Design and Fabrication: Leveraging numerical simulations, computational methods, and surrogate machine learning to create bioinspired and efficient robotic designs.
• Reinforcement Learning and Machine Learning: Applying data-driven approaches to enable robots to learn and adapt to new tasks and environments.
• Autonomous Vehicles and Transportation Networks: Focusing on planning and control strategies for autonomous cars and integrated transportation systems.
• Motion Planning and Control: Developing advanced algorithms for autonomous navigation, control, and decision-making in dynamic environments.
• Safety-Critical Robotic Systems: Ensuring high performance and reliability in robots operating in uncertain and variable conditions, particularly in systems involving human interactions.