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their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in
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on remote sensing of air quality. Emphasis will be placed on using satellite observations to understand the impacts of wildfires and prescribed burning on air quality. The candidatemust have a Ph.D. in a
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the fields of Artificial Intelligence (AI) and Earth Observation (EO). It has extensive experience in remote sensing, particularly in radar imaging and its application for measuring surface displacement. It
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of the ZTW under the supervision of the HAITrans research group leader Univ.-Prof. Dragoș Ciobanu, PhD. Your personal sphere of play: Your future position is within the HAITrans research group (https
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: This position will be a one (1) year full-time term limited appointment with the possibility of renewal. Integrate survey and administrative datasets with environmental data (e.g., remotely sensed
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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2
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Are you passionate about integrating agronomic, genomic, and remote sensing data to better understand plant stress, disease progression, and crop resilience? Do you enjoy working across field campaigns
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 6 days ago
-peter-lab-index.html Your tasks Building large scale foundation models Applying and further developing single cell segmentation methods Supervising a small team of PhD and MSc students Developing new
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for healthcare and dependent care expenses Responsibilities* Integrate survey and administrative datasets with environmental data (e.g., remotely sensed temperature and air pollution) Perform econometric analyses
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collaboration with the division of Geoscience and Remote Sensing at Chalmers. The project is funded by the European Research Council (ERC) under the MIXCLOUDS project, with the following objectives: -Advance our