PhD - Data-driven Optimization of Industrial Wireless Networks and Applications

  • Robert-Bosch-Campus 1, 71272 Renningen, Germany
  • Full-time
  • Legal Entity: Robert Bosch GmbH

Company Description

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology – with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

Job Description

With the development of future cellular 5G standards, wireless networks are expected to play a disruptive role in the whole area of manufacturing. Such applications as mobile robotics and edge-cloud control can provide new levels of flexibility and efficiency not possible with current networking technologies. Configuration and optimization of such networks and applications is a very challenging task in industrial environments taking into account dynamic nature and strict requirements of many applications.
The aim of the PhD is to investigate, implement and evaluate learning methods, based on both detailed network measurement data as well as system context data, to optimize end-to-end performance on distributed industrial applications.
We are looking for a candidate eager to obtain an industrial PhD and strengthen our research team in the area of machine learning for wireless communications. The position is placed within the EU ITN WindMill project, which offers an excellent research and training program (WindMill ITN project website: https://windmill-itn.eu/).

  • Experience cooperation: You will be primarily hosted by Corporate Research of Robert Bosch GmbH in Renningen (Germany) with extended stays in partner institutions. The training program including regular summer and winter schools to build technical skills as well as soft skills.
  • Networked communication: You have the opportunity to join a network of leading universities, research institutes and companies in the field of wireless communications and machine learning.

Due to specifics of this scientific EU-program all candidates must meet the following requirements to be considered for this post:

  • At the time of recruitment shall be in the first four years of their research careers and not yet have been awarded a doctoral degree.
  • At the time of recruitment, must not have resided or carried out their main activity (work, studies) in Germany for more than 12 months in the last three years.

Qualifications

  • Education: excellent Master degree in computer/electrical engineering, information technology, mathematics or related
  • Experience and Knowledge: significant knowledge in communication and networks technology, especially layer 2 and above, good understanding of statistical fundamentals (statistical inference, time series analysis, Bayesian statistics, Markov chains), ideally first practical experience with some machine learning approaches (for example, generalized linear models, random forest, neuronal networks, reinforcement learning), solid experience with programming languages (C++, Python, Matlab, R), comfortable with Linux fundamentals and networking tools
  • Personality: team player with independent thinking eager to learn and solve novel and hard problems
  • Working Practice: result-oriented and innovative
  • Languages: excellent in English (written and spoken)

Additional Information

Duration: 3 years

The final PhD topic is subject to your university.You will be enrolled in the PhD program at Aalborg University (Denmark).

Please submit all the following relevant documents:

  • Your cover letter describing the motivation for applying to the position.
  • Your curriculum vitae including education qualifications, research and industrial experience, awards and fellowships, any additional scientific achievements.
  • A copy of your Master degree certificate (or equivalent).
  • An official transcript of the completed subjects and grades achieved in the course of your Master degree.
  • A documentation of your English skills (TOEFL, IELTS, CAE or CPE)

The salary is very competitive and complemented by mobility or family allowance.
                                                            
Need support during your application?
Kevin Heiner (Human Resources)
+49 711 811 12223

Need further information about the job?
Nikolaj Marchenko (Functional Department)
+49 711 811 24518

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