Fraunhofer-Gesellschaft

Scientific Research Associate – Machine Learning, Sensor Systems

Fraunhofer-Gesellschaft

full-time

Posted on:

Location Type: Office

Location: München • Germany

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Tech Stack

PythonPyTorchTensorflow

About the role

  • Development and implementation of machine learning and deep learning models for the analysis of sensor data
  • (Pre-)processing and analysis of time- and frequency-domain sensor data (signal processing, feature engineering)
  • Design and maintenance of data pipelines: sensor data acquisition, storage (e.g., databases) and preparation
  • Use of Python (including TensorFlow, PyTorch) for ML applications, model training, evaluation and deployment
  • Use of GPU-based servers and modern IT infrastructure for training and inference
  • Application of classical ML methods (e.g., regression, classification) as well as neural networks (e.g., CNNs, RNNs)
  • Preparing ML models for inference on edge systems (Edge AI, Embedded AI)
  • Contributing to MLOps/DevOps processes (e.g., versioning, automation, CI/CD)
  • Collaboration in national and international research projects
  • Publishing results in peer-reviewed journals and at conferences
  • Creating structured technical documentation of development results

Requirements

  • Successfully completed academic degree, preferably in Computer Science, Electrical Engineering or a comparable field
  • Excellent programming skills in Python (e.g., TensorFlow, PyTorch)
  • Solid knowledge in Machine Learning / Deep Learning (statistics and data analysis)
  • Good knowledge of sensors and sensor technology or sensor applications
  • Experience working with sensor data and sensor networks, including data acquisition, storage and processing
  • Ideally, initial experience with DevOps/MLOps approaches
  • Techniques for reducing ML model size and complexity to enable execution on constrained hardware
  • Strong analytical and solution-oriented thinking
  • Independent, structured and responsible working style
  • Very good communication skills for collaboration with industry partners and project teams
Benefits
  • Opportunity to pursue a PhD
  • Work in an interdisciplinary and committed research team
  • Access to modern computing resources and research infrastructure
  • Flexible working hours and opportunities for personal development
  • Remuneration according to TVöD EG 13 (depending on qualifications)
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningdeep learningPythonTensorFlowPyTorchsignal processingfeature engineeringMLOpsDevOpsdata analysis
Soft Skills
analytical thinkingsolution-oriented thinkingindependent workingstructured workingresponsible workingcommunication skills