7 kalman uni jobs

Microfluidics for Characterization of Complex Fluids

240.688.7883 Kalman Migler [email protected] 301 956 0555 Frederick R. Phelan [email protected] 301.975.6761 Paul Francis Salipante [email protected] 301-975-2820 Description We

Aeroelastic Reduced-Order-Model for Real-Time Data Assimilation.

problems and built using simulation data. This data will be generated using a inhouse code. Once these inexpensive models are built, one will use classical data assimilation techniques, such as Kalman

PhD Fellow in “Mission Planning for Cooperative Unmanned Maritime Systems towards UXO Survey

., Kalman, extended Kalman and particle filters Programming languages such as e.g. Python, C++ and LABVIEW Experience with Robot Operating System (ROS) In the assessment, the emphasis is on the applicant's

Data Assimilation Scientist - 128082

and Kalman filtering techniques. Skills to communicate complex information in a clear and concise manner both verbally and in writing. Skills in visualization and graphical representation. Experienced

Doctoral student in Machine Learning for Dynamical Systems

strive to develop data-driven state estimation and tracking methods beyond Kalman and Particle Filters. We will also develop classification and clustering of complex dynamical processes. The associated

Senior Mechatronic Engineer, School of Molecular and Life Sciences

with Git and GitHub. Experience in machine development and automation. Familiarity with a range of sensors, actuators, and control systems. Experience in the application Kalman filtering is highly

Robotics Engineer for Construction Mobile Robot at Gramazio Kohler Research

, etc) Experience with state estimation (sensor fusion, Kalman filters, etc) Experience with deep learning software (PyTorch, TensorFlow, etc) Experience with deep reinforcement learning algorithms and