Climate Change AI

We are hiring for two new roles in London! Come build with us! If you have experience with geospatial AI/machine learning, please apply below 👇 - Geospatial Data Engineer https://lnkd.in/efKpjNZm - Data Scientist https://lnkd.in/eYGCrubr 🌍 #ClimateTech | 🌱 #GreenJobs | 💼 #Hiring #methane #machinelearning #geospatial #climatejobs #eojobs

We want to share our paper "Towards more efficient agricultural practices via transformer-based crop type classification" which has been accepted at the #ClimateChangeAI workshop at #NeurIPS2024! 🎉 In this paper, we use time series transformers to improve crop classification from satellite imagery in Jalisco, Mexico -- critical work for food security and climate adaptation. Great job of my colleagues Isabella Smythe, Yazid S. Mikail , Mike Smith, and Daisy Nyang'anyi #CCAI #AI4Good https://lnkd.in/eStNtPfn

Exciting opportunity to start a #PhD or #PostDoc Fellowship in #Environment and #Sustainability! 🌏Are you passionate about AI-driven research in Environment and Sustainability? 💡Apply to the ETH AI Center #Fellowships program and join a cutting-edge community where you can collaborate with our world-class faculty and push the boundaries of sustainable innovation: Benedikt Soja, Florian Dorfler, Jan Dirk Wegner, Jonas Peters Konrad Schindler ,Catherine De Wolf, Andreas Krause, Davide Scaramuzza, Elliott Ash, Giorgia Ramponi, Florian Tramèr,Martin Vechev, Mennatallah El-Assady, Simon Mayer, Sebastian Schemm, and many more. 🚀Why a #PhD or #PostDoc Fellowship at ETH AI Center? 🔹 Conduct groundbreaking research at the intersection of AI and environmental sustainability 🔹Collaborate in an inspiring, interdisciplinary environment 🔹Drive impactful solutions for a sustainable future 🔗 Don’t miss this chance to advance your career while contributing to global challenges. 🔗 Learn more and apply now: https://ai.ethz.ch/apply #PhDFellowship #Postdoc #ETHAICenter #Environment #Sustainability #ResearchOpportunities #AIforGood ETH Zürich, Department of Computer Science (D-INFK), ETH Zürich, Department of Environmental Systems Science (D-USYS), ETH Zürich

I am #hiring a Data Scientist based in the EU with experience in AI-driven weather and climate simulations and their applications to study and mitigate risks. If you are interested, please apply here: https://lnkd.in/ezaCS48h

I’m excited to share a fantastic opportunity for a postdoctoral researcher position at NYU’s Courant Institute. We're looking for someone passionate about the crossroads of machine learning, atmospheric processes, and climate modeling. This role is supported by the Department of Energy through our UNSHADE project, which focuses on improving our understanding of shallow clouds and their evolution into deep convection, with the ultimate goal of enhancing their representation in climate models. For more details and to apply, please check out the link below. If you have any questions or need more information, feel free to get in touch! https://lnkd.in/dBQb-sbz

The AI Gambit: Leveraging Artificial Intelligence to Combat Climate Change by Cowls, Tsamados, Taddeo, and Floridi raises an interesting question: How can we ensure #AI not only helps but also drives meaningful, scalable climate action? 🌱 Primarily due to the need to infer a large quantum of model parameter values during training, the computational cost of executing models at scale can be significant. However, for me, this challenge also represents a major opportunity. By advancing techniques such as sparsity methods, low-rank approximations, and dimensionality reduction of data sets, we can drastically reduce resource demands without compromising performance. Innovation and sustainability should go hand in hand. This is where the real opportunity lies: not just in #AI’s raw power, but in applying it strategically to deliver measurable value to businesses and scale industrial sustainability efforts. 🌿 Paper : https://lnkd.in/eszBGDid #ClimateChange #Sustainability #Innovation #ArtificialIntelligence #AIForClimate #CarbonReduction #MavarickAI

🌟 Open Postdoc Position at our team at BIFOLD - Berlin Institute for the Foundations of Learning and Data (salary grade 14 TV-L for 4 years)🌟 We are looking for a Postdoctoral Researcher interested in foundation models for Earth observation. The research topics include (but are not limited to): - Parameter-efficient finetuning of foundation models for remote sensing data; - Model distillation of foundation models; - Continual learning in foundation models. Please check the requirements below and contact me if you are interested via email (demir@bigearth.eu). Requirements: - Successfully completed a doctorate (PhD) with a focus on data management, scalable data analysis, machine learning. - Scientific experience (as demonstrated via relevant scientific publications and solid knowledge in theoretical and applied/practical computer science). - Excellent programming skills in Python and solid knowledge of common machine learning frameworks such as PyTorch or TensorFlow.

📢 CALL FOR PAPERS: #ArtificialIntelligence for #Energy Management in #Buildings and #Cities 🏦 🏗️ 🌏 We have extended the submission deadline for contributions to this special collection to be published in Data-Centric Engineering (an open-access journal at Cambridge University Press & Assessment) in 2025. Buildings account for 40% of the global energy consumption and 30% of the associated greenhouse gas emissions, while also offering a 50–90% CO2 mitigation potential. #Decarbonization strategies will require faster, tighter and more widely coordinated control of energy resources in buildings and cities at multiple spatiotemporal scales: from milliseconds and single components to decades and across geographic regions. The complexity of this problem necessitates automated processes to situational awareness and decision making. This special collection calls for contributions that explore the application of data-driven methods to improve the resiliency and efficiency of the building environment as #engineering system, especially the energy systems. 📆 Submit by 31 January 2025 ℹ️ How to contribute: https://lnkd.in/esTgfc3V Example topics: ✅ Challenges and Opportunities for AI in Buildings, grid, transportation, and Smart Cities ✅ Explorations of model vs model-free algorithms and hybrids ✅ Comparisons of algorithms for control tasks, i.e., MPC vs RL ✅ Frameworks and datasets for benchmarking algorithms ✅ Theoretical contributions brought about by constraints/challenges in the buildings cities domain ✅ Human building interactions (occupant-centric controls, human integration, humanin- the-loop systems) ✅ Applications (digital twins, demand response, HVAC control, traffic scheduling, EV/battery charging, DER integration) Result and analysis of applying model-free and model-based algorithms in real world case studies ✅ Smart, adaptive power electronics ✅ Virtual power plants Editors: Zoltan Nagy (The University of Texas at Austin), Helia Zandi (Oak Ridge National Laboratory), June Young Park (The University of Texas at Arlington) & Mario Bergés (Carnegie Mellon University)

Thrilled to announce that the Second Edition of our AI for Climate Change Mitigation Roadmap just dropped today at COP29 in Baku. The best place to find it is here: https://lnkd.in/eqCahQh3 It shows our 5 takeaway messages and provides access to both the executive summary and the full 334 page report. Many thanks to David Sandalow, Colin McCormick, Julio Friedmann, Michal Nachmany, PhD, Hoesung Lee, and the dozens of co-authors who helped pull this together. This work was sponsored by Japan's Innovation for Cool Earth Forum, Ministry of Economy, Trade and Industry, and New Energy and Industrial Technology Development Organization (NEDO). #ai #climatechange #cop29