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IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH (IMMS GmbH) Tech Stack

Microelectronics and mechatronics research institute bridging embedded systems and industrial applications

Research Services Ilmenau, Thüringen 51–200 employees Founded 1995 Nonprofit

IMMS is a nonprofit research institute in Ilmenau focused on applied microelectronics, sensor systems, and mechatronics for industrial SMEs. The tech stack—C/C++, MATLAB, Simulink, FPGA design (Verilog/VHDL), and embedded protocols (I2C, USB)—reflects deep hardware and control-systems work. Current hiring is almost entirely interns and junior roles in engineering and research, paired with active projects in wireless sensor characterization, IoT power optimization, and image-sensor evaluation. The pain-point surface (timing constraints, energy efficiency, multi-node synchronization) maps directly to embedded systems scaling challenges.

Tech Stack 22 technologies

Core StackMATLAB Python Rust TypeScript Active Directory C/C++ dSpace Simulink PySide6 Qt LabVIEW I2C USB OMNeT++ FPGA Verilog VHDL DATEV Visual Studio Code CMOS z3

What IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH (IMMS GmbH) Is Building

Challenges

  • Timing constraint compliance
  • Optimizing digital circuit area and performance
  • Scalability of on-device learning
  • High-accuracy time synchronization
  • Limited energy supply of wireless sensor nodes
  • Optimizing component values
  • Energy consumption of iot sensor nodes
  • Reducing laser shutdown time
  • Ensuring comparability of sensor data
  • Inaccurate analog value generation and measurement

Active Projects

  • Nanopositioning system performance characterisation
  • Automatic module detection concept
  • Optical measurement of washing media contamination
  • Netlist annotation process
  • Characterization of existing image sensors
  • Python package development for netlist carpentry plugin
  • Prototype implementation of time synchronization
  • Framework development for multi-node wireless sensor system
  • Component value optimization algorithm
  • Measurement concept for iot node components

Hiring Activity

Accelerating35 roles · 15 in 30d

Department

Engineering
19
Research
16
Finance
1

Seniority

Intern
34
Junior
1
Mid
1
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About IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH (IMMS GmbH)

IMMS entwickelt anwendungsorientierte Forschung und Entwicklung in Mikroelektronik, Systemtechnik und Mechatronik für mittelständische Unternehmen. The institute operates as a bridge between Technische Universität Ilmenau and industry, delivering solutions from feasibility study through series production. Core competencies span sensor and actuator systems, signal processing, control systems, and system integration—with particular depth in high-temperature sensors, biomedical sensors, and energy-autonomous wireless systems. The organization employs approximately 80 staff and supervises up to 40 students annually in practice-oriented roles.

HeadquartersIlmenau, Thüringen
Company Size51–200 employees
Founded1995
Hiring MarketsGermany

Frequently Asked Questions

What is IMMS GmbH's tech stack?

C/C++, MATLAB, Simulink, FPGA tools (Verilog, VHDL), Python, Qt, LabVIEW, dSpace, and embedded protocols (I2C, USB). Also uses OMNeT++ for network simulation and z3 for constraint solving.

What projects is IMMS working on?

Active work includes nanopositioning characterization, IoT wireless sensor frameworks, image-sensor evaluation, time-synchronization prototypes, energy optimization for battery-constrained nodes, and Python tooling for circuit netlist processing.

How this profile is built

IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH (IMMS GmbH)'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.