Description
Job Overview
As the Lead Engineer for Low Observability Calculations at Helsing, a defence AI company, you will direct the high-fidelity Radar Cross Section (RCS) simulation workflow. This involves constructing complex analysis models and managing extensive sweep campaigns on high-performance computing clusters. Your primary objective is to generate critical signature data and hot-spot analyses to guide trade studies and shape the low-observable design of the airframe, antennas, and other key features.
Responsibilities
- Direct high-fidelity RCS simulations using MoM and MLFMM for airframe and payload-driven signature topics
- Implement Physical Optics analyses for electrically large structures and fast-turn trade studies
- Construct and maintain analysis models, managing CAD cleanup, material assignment, boundary conditions, and excitation setups
- Create and optimise triangular surface meshes to ensure convergence and numerical stability
- Conduct sweep campaigns across frequency, aspect, and polarisation to generate actionable deliverables including RCS polars and sensitivity studies
- Diagnose and resolve solver issues such as convergence, mesh quality, and numerical artefacts
- Guide signature-reduction trade studies collaboratively with structures and low-observability teams
- Correlate simulation results against range and anechoic measurements, quantifying error bars and documenting assumptions
- Optimise workflows for high-performance computing execution to automate result post-processing
- Produce comprehensive program artefacts and clear, decision-ready reports for design reviews
- Coordinate supplier activities for RCS calculation and testing
Requirements
- Hold a degree in Aerospace Engineering, Electrical Engineering, Systems Engineering, or a related discipline
- Have delivered computational electromagnetic and RCS analysis for complex aerospace platforms, including materials and radome modelling
- Possess practical expertise with MoM/MLFMM and Physical Optics methods, demonstrating when to apply each
- Are proficient in meshing and CAD-to-solver workflows, capable of diagnosing and resolving geometry-driven numerical problems
- Can coordinate large sweeps on high-performance computing clusters, applying an understanding of solver scaling and convergence controls
- Communicate complex results effectively to provide clear design guidance, hotspot attribution, and trade-offs
Nice to Have
- Understand extensions such as PTD, UTD, and edge diffraction methods
Benefits
- Competitive salary and VSOP options
- Relocation support: up to €2,500 and 4 weeks temporary accommodation
- Learning: €500/£450 yearly allowance
- Health and wellness: gym membership and mental health support (Nilo.health)
- Social: regular company events and monthly social allowances
- Enhanced parental leave: 22 weeks fully paid for primary caregivers and 6 weeks for secondary caregivers
- Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work