Bachelor's degree in computer science, electrical engineering, mathematics, statistics, operations research, or related field
Experience with the complete software lifecycle for embedded systems
Strong technical writing and oral communication skills
Demonstrated contributions and expertise in two or more of the following domains: o Regression algo for interpolation and extrapolation (both linear / non-linear) o Time series analysis and statistics, autoregressive models, filtering algorithms o Gaussian processes and/or kernel methods, Bayesian statistics o Modeling with different neural network architectures: MLP, CNN, RNN o Quantitative model performance assessment using cross-validation, blind testing. o Physics-informed neural networks (ML for computational fluid dynamics or finite element analysis, point cloud or mesh-based neural networks, PDE surrogate modelling) o Uncertainty quantification and propagation for time series analysis and forecasting.