-
; Machine Learning• Clinical pathways and decision support for patients with acute chest pain• AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis• Speaking
-
), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas, SHAP, TensorFlow, etc.) y específicas de análisis de imágenes, estadística, simulación, entornos cloud (tipo Kubernetes
-
positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
-
to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
-
, multisignal patches and wireless devices. Design and development of algorithms for multimodal biomedical signals based on Personalized Models, Deep Learning and Explainable AI. Applications to respiratory
-
environment representations, deep reinforcement learning, and intelligent robotic behavior. Solutions will be validated in simulation (e.g., ROS/Gazebo, Isaac Sim) and real robotic platforms. The candidate is
-
Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
-
Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
-
measurement, four-point probe for resistivity, deep-level transient spectroscopy, and a semiconductor parameter analyzer. Job Description: The Department of Electrical and Computer Engineering (ECE
-
internally, so while you learn the intricacies of our industry, you’ll have plenty of opportunities to contribute and directly affect our bottom line within your first few weeks on the team. While interest in