Research Scientist - Natural Polymers and Bio-Based Materials

SVERIGES LANTBRUKSUNIVERSITET

Department of Forest Bioeconomy and Technology Do you want to help shape the future of sustainable materials? We are seeking a highly motivated postdoctoral researcher to advance the design of next-generation bio-based adhesives that meet both sustainability targets and industrial performance requirements. In this project, you will combine cutting-edge approaches in polymer science and AI-driven modelling to develop predictive frameworks and high-performance adhesive systems for furniture, construction and packaging industries. You will work at the interface of fundamental science and real-world application, contributing to the transition toward a more sustainable materials economy. If you have a strong research background and a drive for innovation, this position offers an exciting opportunity to take the next step in your academic career! The recruitment is done within the BioGlue-Centre “Competence Centre for Bio-based Adhesives”, which is a Vinnova Competence Centre in Sustainable Industry and Digital Transformation. The vision of the Centre is to significantly reduce the dependency on fossil-based materials in the adhesive industry by developing paradigm-shifting knowledge of bio-based adhesives and becoming a world-leading research environment in Sweden. It is built around a network of top-scientists with expertise in polymer science, adhesives, technology, and sustainability located at the Department of Forest Bioeconomy and Technology at SLU (https://www.slu.se/en/about-slu/organisation/departments/department-of-forest-bioeconomy-and-technology/), the Department of Fibre and Polymer Technology at KTH (https://www.kth.se/fpt/fibre-and-polymer-technology-1.778696), and the Department of Forestry and Wood Technology at Linnaeus University (https://lnu.se/en/meet-linnaeus-university/Organisation/faculty-of-technology/meet-the-faculty-of-technology/forestry-and-wood/). The Centre unites 13 companies along the value chain in furniture, packaging and construction sectors that share the same research questions around adhesives and adhesive bonding. About the position The development of bio-based adhesives is currently limited by a lack of predictive understanding of how formulation chemistry translates into material performance. This project addresses this challenge by establishing a data-driven framework for the rational design of high-performance bio-adhesives. As a postdoctoral researcher, you will work on integrating experimental formulation, molecular-level characterization, and machine learning to develop predictive models linking chemical descriptors to adhesive properties. The work includes the development of a structured formulation library, systematic mapping of key performance indicators, and the implementation of data-driven optimization strategies to identify high-performing systems. Machine learning approaches will be used to uncover structure-property relationships and guide formulation design. The project combines experimental and computational approaches and includes validation of selected formulations on industrially relevant substrates. You will collaborate closely with academic and industrial partners and contribute to the development of a transferable predictive toolbox for next-generation sustainable adhesives. Your profile We are seeking a highly motivated postdoctoral researcher with a doctoral degree obtained within the last three years in materials science, polymer science, chemistry, chemical engineering, or a closely related field. The ideal candidate has strong expertise in polymer formulation and structure-property relationships, particularly in the modification and crosslinking of bio-based or functional polymers for adhesive or related applications. Experience with advanced material characterisation techniques is expected. A strong interest in data-driven research is essential. Experience with modelling approaches, data analysis, or machine learning applied to materials or chemical systems is considered a strong merit. You are expected to have excellent communication skills in English, both written and spoken, and a clear motivation to pursue an academic career. The ability to work independently, take initiative, and collaborate effectively in an interdisciplinary and international research environment is essential. In the evaluation of candidates, particular emphasis will be placed on (1) scientific excellence in polymer and materials science, (2) experience or demonstrated potential in applying machine learning and data-driven approaches to materials or formulation design, and (3) the ability to contribute to and expand ongoing research activities within the group. About us The Department of Forest Bioeconomy and Technology at SLU brings together expertise in technology, natural and social sciences. The department provides world-class interdisciplinary environment for research and education in the circular bioeconomy, with activities at the campuses in Umeå and Uppsala, and nationally and internationally. Our work spans the entire value chain of the forest-based bioeconomy – from analysing how resources can be used and governed to developing technologies, materials, and industrial processes for sustainable bio-based products and systems. The Department is responsible for education at the bachelor’s, master’s, and doctoral levels and collaborates closely with both industry and academia nationally and internationally. With us, you can help shape a more sustainable bio-based society. For more information about the department or division visit: https://www.slu.se/om-slu/organisation/institutioner/skoglig-bioekonomi-och-teknologi/?gad_source=1&gad_campaignid=21086656031&gclid=EAIaIQobChMIwMj3yOmalQMVdluRBR3n7yxAEAAYASAAEgKD_fD_BwE Read more about our benefits and working at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment: Temporary employment 24 months, with the possibility of extension. Scope: 100% Start date: The position may start as agreed between both parties but not later than January 1, 2027. Application: Please submit your application before deadline 16 August 2026. You can submit your application by clicking the button below. Union representatives: https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/

Prior Labs

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. ABOUT THE ROLE Tabular data breaks the assumptions that make scaling work for language and vision. There's no natural sequence, no spatial structure, no shared vocabulary across datasets. The architectures and scaling laws that power LLMs don't transfer. We've made the first breakthrough with TabPFN — but the hardest problems are still ahead. At Prior Labs, Research Scientists drive the core model agenda. You'll define research directions, design novel architectures, and publish work that advances the field — while ensuring your ideas translate into models that actually ship. We create cutting-edge models because the same people do both. As an early team member, you'll have significant technical ownership and room to grow as we scale. The problems we're solving: * Scaling transformer architectures from 10K to 1M+ samples — without the structural assumptions that make language models scale * Building multimodal models that combine tabular, text, and numerical understanding * Making models efficient enough for real-world deployment — not just accurate enough for a paper * Designing architectures for time series, forecasting, anomaly detection, and multiple related tables * Researching causal understanding in foundation models What We're Looking For * PhD in Computer Science, Applied Mathematics, Statistics, Electrical Engineering, or a closely related field, or equivalent research experience with demonstrated impact * Publications at top-tier ML venues (NeurIPS, ICML, ICLR, etc.) or equivalent impact through widely used open-source, benchmarks, or deployed systems * Strong experience building and analyzing machine learning models, including transformer or other sequence-based architectures, using PyTorch * Solid understanding of training dynamics, generalization, scaling behavior, and common failure modes in deep learning systems * Excellent engineering fundamentals and strong Python skills, with a track record of writing high-quality research code Nice to Have * Experience at an early-stage startup or research lab with a shipping culture * Contributions to open-source ML libraries or tools * Experience with model distillation, inference optimization, or efficient architectures * Background in tabular data, time series, or other structured data — helpful but not required Life at Prior Labs We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with. We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together. Our Commitments We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box." We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.

Zora Ecosystems

WHO ARE WE? Zora Ecosystems’ mission is to regenerate natural ecosystems responsibly so that the planet and its communities can thrive.  We combine proprietary technology and domain expertise with on-the-ground relationships to mobilise landowners, major infrastructure providers, investors, government bodies, and communities around large-scale nature restoration programmes.      Zora Ecosystems accelerates nature recovery using data, technology, and rigorous science. Doing the right thing for nature and people is at the heart of our work, and we apply peer-reviewed and novel scientific methods to scope, plan, and support the delivery of on-the-ground regeneration projects. We build systems that enable ecosystem restoration at scale, blending interdisciplinary scientific expertise with geospatial analytics and environmental data science. We combine our technology and domain expertise with on-the-ground relationships to mobilise landowners, investors, government bodies, and communities around large scale nature restoration programmes.   We are a venture-backed scale-up entering a new phase of growth. After our success working with landowners to deliver projects on the ground, we are now expanding to the demand side of the market. Partnering with large corporates and regulated utilities providers, we will be providing landscape level solutions across a wide range of nature-based interventions, targeting a broad scope of outcomes that includes water quality, flood risk, carbon sequestration, biodiversity uplift and many more.   WHAT WE STAND FOR  NATURE: Nature is at the heart of everything we do. It grounds our decisions, reminds us of the interconnected systems we’re part of, and inspires us to design with care, responsibly, and with long-term thinking. By staying close to nature, we stay close to what truly matters: impact that creates nature-positive outcomes.  INNOVATION: Innovation drives our curiosity, courage, and our ambition. We experiment with science and technology to support us in challenging convention. For us, innovation isn’t about being novel — it’s about creating meaningful progress now for a better tomorrow.  TRUST: Trust is the foundation of Zora Ecosystems. We build it through internal engagement with our teams and externally with our clients. People can rely on us to do the right thing, every time. When trust is strong, everything else becomes possible. Trust is the main building block of high-performing teams.  We are growing our capabilities on landscape approaches to nature restoration and land use, particularly focused on solving grand challenges related to water. We are working with water companies, NGOs and local councils to design and deliver large-scale nature restoration projects that improve outcomes in flooding, drought and water quality. YOUR MISSION We’re seeking a versatile and outcome-focused researcher with expertise in sciences relating to water supply management, flooding, hydrology, or hydraulic modeling to develop novel and scalable nature-based solutions approaches for grand challenges in the water space.     In this role you will combine the best in academic research with industry tech to develop novel models and methods to which improve water outcomes by restoring ecosystems. Your models and insights will inform real-world landscape regeneration projects, improve biodiversity outcomes, and address the impacts of climate change. Working closely with a multi-disciplinary team of scientists and field practitioners, your work will have a real positive impact on people and the planet.     As part of our R&D team, you will work under our Head of Applied Science and our Senior Water Scientist to quantify how nature-based solutions can help mitigate drought and flooding at multiple spatial scales - from landholding to catchment and landscape scales. You will build scalable modeling approaches that can be applied nationally and internationally. In due course, you’ll develop approaches to integrating hydrological and hydraulic models with other types of natural process models (such as models relating to soils, peat and biodiversity), and climate model data.       You will:   * Apply remote sensing data, in situ data, and hydrological and hydraulic models to understand water dynamics at the catchment and sub-catchment scales. * Co-design landscape interventions to reduce flood risk, mitigate drought, improve water quality, and build new habitats in collaboration with your science team colleagues and our team of field experts. * Gather ground-truth data to validate desk-based model analytics.   * Develop partnerships and collaborations with academic research groups, water companies, and other businesses in the field of water science. * Contribute to improving internal models and research on nature restoration.   * Apply your geospatial knowledge and skills to solving other landscape-level scientific challenges. * Mentor junior science staff and regularly supervise interns.  YOUR PROFILE Requirements:   * A passion for making a positive impact on the planet and solving grand environmental challenges * A PhD, or equivalent level of experience, in a discipline related to catchment scale hydrology, nature-based solutions, water science, hydraulic modeling, hydrogeology, physics, remote sensing, engineering, or other similar fields. * Experience working in Python * Knowledge of processing techniques and manipulation of GIS datasets: proficiency in GIS mapping data and software, and experience in geospatial data analysis.   * Experience using relevant geospatial data types, such as LiDAR and land cover. * Proactive, methodical, and data-driven approach to problem-solving.  * Enthusiasm for working collaboratively with teams comprising different scientific and non-technical backgrounds * The ability to communicate complex technical topics effectively to a non-technical audience Nice to haves:   * Experience or expertise in hydraulic or hydrological models, hydrogeology or ground water, soil science, or nature-based solutions relating to these * Experience with AWS or other cloud computing environments, and large geospatial datasets (e.g. using cloud-optimised format, manipulating high-resolution spatial data, etc.) * Experience or expertise in natural capital assessment WHY US? For more information on our ways of working, culture, and mission, please refer to: https://careers.zora.eco/