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4 дня назад

PhD Student (d/f/m) Intelligent Process Monitoring and Digital Twinning (Cold-Sprayed Repair Applications)

Формат работы
onsite
Тип работы
fulltime
Грейд
trainee
Английский
c1
Страна
Germany
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
PhD Student (d/f/m) Intelligent Process Monitoring and Digital Twinning (Cold-Sprayed Repair Applications): Developing a real-time, data-driven monitoring framework for cold-sprayed metallic component repairs with an accent on sensor-based data acquisition, machine learning, AI, and digital twin integration. Focus on detecting process deviations, modeling physical process behavior, building large-scale data pipelines, and validating the monitoring system in an industrial aerospace environment.

Location: Manching, Germany; on-site PhD position with a 36-month duration and a possible research stay at a European partner institution.

Salary: Attractive salary; exact amount not specified.

Company

hirify.global develops aerospace and defence technologies, including advanced materials and manufacturing processes.

What you will do

  • Review sensor-based methods for detecting process irregularities and anomalies in cold-sprayed repairs.
  • Identify and integrate sensors for capturing process signals correlated with deposition parameters.
  • Build data acquisition and preprocessing pipelines for large-scale datasets.
  • Develop machine learning and AI models for recognizing process patterns and quality deviations in real time.
  • Create a digital twin framework connecting monitoring data with physical process behavior.
  • Validate and demonstrate the complete monitoring pipeline in an industrial setup, including reliability evaluation and scientific publications.

Requirements

  • Completed Master’s degree in Computer Science, Mechatronics, Physics, Data Science, engineering, natural sciences, or a related field.
  • Strong knowledge of data signal processing and machine learning.
  • Programming experience with Python, MATLAB, or C++; familiarity with TensorFlow, PyTorch, or Scikit-learn is desirable.
  • Analytical thinking, creative problem-solving, and the ability to model complex physical phenomena.
  • Ability to work across interdisciplinary materials, manufacturing, data, and process-monitoring challenges.
  • Excellent written and spoken English is required. German is an advantage.

Nice to have

  • Basic understanding of manufacturing processes or materials science.
  • Experience with ML libraries such as TensorFlow, PyTorch, or Scikit-learn.

Culture & Benefits

  • 35-hour working week with flexitime.
  • International environment with opportunities for global networking.
  • Access to modern and diversified technologies.
  • Participation in the Generation Airbus Community.
  • Travel within Germany or overseas may be possible after departmental agreement.

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