Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
. • Contribute to interdisciplinary research projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep
-
issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning
-
, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
-
Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
-
models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical
-
a two-year research project in collaboration with international academic partners. The main objective of the project is to study the interaction between machine learning and wireless communication
-
of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
-
techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics. Responsibilities of the Position The Postdoctoral researcher is intended to support the soil spectroscopy research activities and digital
-
SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
-
The successful candidate will contribute to the following research axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate