ReScience provides specialized technical consultancy, R&D support and engineering training in signal processing, RF sensing, autonomous systems, embedded technologies and related advanced engineering fields.
We work closely with customer engineering and R&D teams throughout the development lifecycle, supporting activities from problem formulation and modelling to algorithm development, simulation, testing, real-data analysis and performance improvement.
Our R&D Consultancy Services
- Technical problem analysis and system-level assessment
- Algorithm development and improvement
- Mathematical modelling and simulation
- Signal and data-processing architecture development
- Performance analysis and benchmarking
- Recorded and experimental data analysis
- Algorithm tuning and optimisation
- Prototype and system-level technical evaluation
- Test and validation support
- Technical documentation and engineering reviews
Embedded Collaboration with R&D Teams
Depending on project requirements, ReScience can work as an integrated technical partner alongside internal engineering teams.
Our collaboration model may include:
Problem Definition → Modelling → Algorithm Development → Simulation → Testing → Real-Data Analysis → Performance Evaluation → Iterative Improvement
This approach is particularly suitable for technically challenging R&D projects where system performance must be progressively improved using simulation, laboratory tests and operational data.
Technical Training
ReScience provides project-oriented technical training tailored to the needs of engineering and R&D teams.
Training topics may include:
- Statistical and digital signal processing
- RF signal detection and parameter estimation
- Antenna-array and multichannel signal processing
- Direction finding and localization
- Modelling and simulation techniques
- Signal-processing algorithm development
- MATLAB and Python-based algorithm prototyping
- Analysis and interpretation of recorded measurement data
- Autonomous and airborne sensing systems
Training activities can be directly connected to an ongoing development project, enabling teams to apply theoretical concepts to their own systems, data and engineering challenges.
Selected Industrial R&D Experience
Between 2022 and 2024, ReScience provided long-term technical consultancy to the signal-processing and algorithm-development team of an industrial airborne RF signal detection and localization programme.
The collaboration included:
- Technical training and knowledge transfer
- Signal-processing and localization algorithm assessment
- Mathematical modelling and simulation
- Analysis of recorded flight-test data
- Investigation of performance limitations
- Algorithm modification and optimisation
- Evaluation of improved algorithms using experimental data
- Technical discussions and engineering support throughout the development process
Rather than providing isolated consultancy, ReScience worked closely with the customer’s engineering team through iterative development and validation cycles.
This experience strengthened our capability to support complex airborne sensing projects in which theoretical algorithms must be adapted to real system characteristics, operational constraints and measured data.
Areas of Expertise
Our consultancy and training activities primarily support:
- RF sensing and signal processing
- Airborne sensing systems
- Direction finding and localization
- Radar and active RF sensing research
- Autonomous and unmanned systems
- Embedded and edge-processing systems
- Distributed sensing and wireless systems
- Signal and sensor-data analysis
R&D Collaboration
ReScience collaborates with technology companies, system integrators and research organisations requiring specialized engineering expertise or additional algorithm-development capability.
We can contribute as a focused technical consultant or as an integrated R&D partner working alongside the customer’s engineering team throughout development, testing and performance-improvement activities.work as an integrated technical partner alongside internal engineering teams.