Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
processes, targeting annual savings of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
profiling (BGC-Argo) floats (https://www.nature.com/articles/s41586-021-03805-8). The NASA Ocean Biogeochemical Model (NOBM) has recently been coupled to the Subseasonal to Seasonal Prediction Version 3 (S2S
-
incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
-
of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real-time data acquisition. You will
-
, version control) and numerical workflows. Experience programming for data analysis and model workflows (e.g., Python, MATLAB; FORTRAN/C familiarity for model configuration). Demonstrated verbal and written
-
Modeling and outputs. Implements Strategic Modeling governance, data-quality controls, and version-management processes. Leadership, Team Management, and Staff Development Directly supervise two Strategic
-
with a strong background in machine learning and LLMs, computer science, and modeling. The candidate will join the project “AI-driven predictive maintenance for buildings: Einar Mattsson (EM) - KTH
-
into the wave interaction and propagation processes. Modelling the propagation characteristics of optical communication systems with a focus on optical atmospheric turbulence and statistical prediction models
-
results but are hampered by large individual differences in response. It is evident that we need to rethink the premises of randomized controlled trials (RCTs) to better predict who will benefit from which
-
. The work is part of the regional project “Optimizing Renewable Energy Integration: FPGA-Based Model Predictive Control (MPC) for Grid Stability” (Ref. SI4/PJI/2024-00238) Where to apply Website https