JuliaHub

• Design and implement symbolic-numeric compiler passes to enhance the Dyad compiler’s ability to handle complex numerical systems. • Develop and optimize algorithms such as dynamic state selection, nonlinear tearing, and Pantelides-based transformations for DAE systems. • Improve compiler handling of strongly connected components (SCCs), including efficient lowering and code generation strategies. • Contribute to code generation and optimization for high-performance execution across multicore CPUs, GPUs, and distributed systems. • Leverage parallelization techniques including SIMD autovectorization, multithreading, and distributed computing.

• Lead and execute services projects with Dyad, including understanding customer requirements, architecting solutions, and delivering comprehensive software solutions to deliver value. • Lead the development of physical, multi-domain system models for industrial applications, focused on thermal, chemical/process, and complex thermofluid domains. • Lead and contribute to the development of new model libraries for Dyad in domains of expertise. • Develop validated digital twins of complex systems by integrating data, system models, and SciML techniques leveraging the full power of Julia and the JuliaHub platform. • Leverage AI and agentic workflows in all aspects of model-based systems engineering processes (i.e. model development, debugging, analysis, deployment, etc.) • Engage as the voice-of-the-customer with the AI team to develop and prototype new AI capabilities integrated into the Dyad platform. • Engage with the Sales team to provide technical presales solutions in domains of expertise and nurture customer relationships. • Integrate controls and model discovery into acausal modeling frameworks. • Design and optimize surrogate modeling techniques (e.g., continuous-time echo state networks, neural ODEs) for automated model acceleration.

• Collaborate with language designers to define the precise semantics of Dyad's synchronous constructs, including clock definitions, data-flow dependencies, state machines, and execution semantics. • Build the compiler front-end and middle-end infrastructure in Julia for Dyad's synchronous programming constructs. • Implement robust clock inference and checking to ensure safe and deterministic data-flow execution. • Develop optimized code generation backends targeting real-time, deterministic execution. • Ensure seamless integration between the continuous-time (ODE/DAE) equation solving and the discrete-time synchronous partitions of the Dyad language. • Work closely with domain and modeling experts to refine the semantics and syntax of Dyad's synchronous features.