Artificial Intelligence

h3Belgium | 5+ years of experience | Hybrid international /h3pFuse observations, sensors and physical models into intelligence that helps water systems anticipate change. /ph3The opportunity /h3pbHAEDES /b is looking for an AI/ML Data Fusion Engineer to strengthen our team in bBelgium /b. We seek someone who can turn complex, heterogeneous data into dependable forecasts, early warnings and actionable insights for rivers, coasts, estuaries, oceans and water-related assets. /ppYou will combine Earth Observation, in-situ IoT measurements and numerical-model outputs to develop predictive models, data-fusion methods and analytical components for scalable environmental applications. Working between applied research, engineering and software development, you will help advance the data-driven intelligence within HAEDES’ digital twins and regenerative blue-economy projects. /ph3What you will shape? /h3ulliDevelop, train and evaluate supervised and unsupervised machine-learning models for environmental and engineering applications. /liliCreate data-fusion methods that reconcile satellite, sensor, geospatial and numerical-model data across different scales, frequencies and uncertainties. /liliBuild time-series forecasting, anomaly-detection and predictive-maintenance or risk-indicator solutions. /liliDesign features and hybrid approaches that combine domain knowledge, physical models and data-driven methods. /liliDevelop reproducible data pipelines for ingestion, quality control, transformation, training, validation and operational inference. /liliQuantify predictive uncertainty, monitor model performance and communicate when outputs are
- and are not
- fit for use. /liliTranslate models into clear demonstrations, visualisations and decision-support components for technical and non-technical users. /liliContribute to RD proposals, client projects and partnerships while exploring promising ideas of your own. /li /ulh3What you bring? /h3ulliA master's degree or PhD in data science, computer science, mathematics, engineering, physics, environmental science or a closely related field. /liliAt least 3 years of relevant experience in data science, machine learning, predictive modelling and/or scientific computing. /liliStrong programming skills in Python and C++, with practical experience in scientific-computing, data-science and machine-learning ecosystems. /liliExperience with supervised and unsupervised learning, statistical modelling, feature engineering and robust model validation. /liliHands-on experience with time-series analysis, forecasting, anomaly detection and predictive modelling. /liliExperience integrating heterogeneous datasets with different spatial and temporal resolutions. /liliThe ability to work efficiently with large datasets and select appropriate storage, processing and exchange formats. /liliA sound understanding of uncertainty, bias, data leakage, generalisation, performance metrics and model limitations. /liliThe ability to explain analytical methods and results to both specialist and non-specialist audiences. /liliProfessional working proficiency in English. (Confirm whether Portuguese is required or preferred.) /li /ulh3Additional experience we value /h3ulliEnvironmental, geospatial, satellite, oceanographic, hydrological or IoT sensor data. /liliNumerical or physical modelling and hybrid, physics-informed or surrogate-modelling approaches. /liliCloud-based and distributed data or ML workflows, including containers, orchestration and scalable inference APIs. /liliMLOps practices such as experiment tracking, versioning, automated testing, deployment, monitoring and retraining. /liliDeep learning, spatiotemporal modelling, computer vision, Bayesian methods or data assimilation. /liliForecasting and early-warning services, asset-specific risk analytics or digital-twin applications. /li /ulh3How you work? /h3pYou are adventurous enough to explore the unknown and rigorous enough to make the result trustworthy. You work autonomously without working alone, challenge assumptions and invite scientists, engineers, software developers and domain experts into the process. You combine creativity with responsibility, treat uncertainty honestly and keep learning as methods, data and environmental questions evolve. /ph3What makes HAEDES different? /h3pHAEDES blends engineering and soul: logic with emotion, knowledge with wisdom, and process with patterns. We address root causes rather than symptoms and co-create solutions inspired by nature. Our values – nature, trust, connection, creativity, autonomy and authenticity – guide how we choose projects, work with partners and make decisions. /pulliA living-system organisation that adapts through co-creation, learning and distributed responsibility. /liliFreedom to pioneer and pursue original ideas, paired with accountability for data quality and useful outcomes. /liliWork at the intersection of water, AI, Earth Observation, numerical modelling, climate resilience