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Algorithm Development Engineer
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Location: Bristol
Job type: Contract
Aircraft type:
Contact: Nick Wallwork
Sector: Engineering, Military & Defence
Job Role:
The position focuses on the design, development and proving of algorithms for missile, Command & Control (C2) and Mission Planning applications. This includes algorithms in the domains of: control, guidance and navigation image processing for EO and RF systems data fusion, classification/pattern-recognition & tracking decision making and motion/route planning for decision support and autonomous systems.
The role may involves aspects of algorithm design and proving analysis of closed-loop model simulations analysis of sub-system and system trials/firing data generation and maintenance of design documents preparation and presentation of material at reviews working with Systems, Simulation & Modelling and Software Engineers to support the integration and validation of algorithm performance and the embedded software.
The hosting department works through the full lifecycle, including research studies and development/certification. The work of the hosting department is broad, and there is scope for existing team members to be moved around to accommodate candidates with particular skills.
Skills and Knowledge:
A background from a numerate discipline (Engineering, Physics, Mathematics, Computer Science, Information Engineering) with strong mathematical and analytical skills is essential. The main toolset used is Matlab/Simulink, but experience in FORTRAN or C would be relevant for legacy products.
Consequently, candidates must be comfortable with developing , testing and working with algorithms/models using such tools. Ideally candidates should have some knowledge/experience of one or more of the following domains:
Flight dynamics, dynamic systems, optimal control, multivariable control, H-infinity, Mu-analysis, guidance systems, trajectory optimisation, estimation/tracking and Kalman filters, integrated navigation, computer vision, image and signal processing for detection and tracking, autonomous systems, pattern-recognition, decision making, artificial intelligence/machine learning.
However, candidates possessing a strong mathematical background who can apply themselves to these domains are also of interest. Candidates from an academic background are suitable.
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