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PhD Position (m/f/d) Analysis and data correlati ... (No replies)

Helmholtz-Zentrum Hereon
5 years ago

The Helmholtz-Zentrum Geesthacht (HZG), in Geesthacht, near Hamburg, and in Teltow, near Berlin, conducts materials and coastal research. For further information please refer to: http://www.hzg.de

HZG is one of the 19 national institutions of the Hermann von Helmholtz Association of German Research Centres e.V. (HGF). Around 1,000 employees carry out basic research and development work in close cooperation with national and international research institutions, research-oriented clinics and economic and public institutions.

At the Institute of Materials Research some 200 scientists conduct research in the five sub-institutes "Materials Mechanics", "Materials Physics", "Materials Technology", "Magnesium Innovation Centre MagIC" and "Metallic Biomaterials".

PhD Position (m/f/d) Analysis and data correlation for the modelling of degradation processes of magnesium under load

Reference code: 50033328_2 – 2020/WB 5
Commencement date: as soon as possible
The place of employment is Geesthacht.

The Institute of Materials Research, Division Metallic Biomaterials at HZG focusses on the development of Magnesium (Mg)-based alloys for specific applications such as biodegradable implants. Especially for biomedical Mg-based devices, it is crucial to understand and model the mechanisms governing the interactions between alloy composition and microstructure on one side and mechanical as well as corrosive properties on the other side. The challenge is the complex biological environment under which the implant has to operate and eventually dissolve. One important piece of additional information is the influence of load on the degradation behaviour under physiological conditions that shall be addressed within the framework of this project.

Within this framework, we are offering a PhD position (m/f/d). The position is initially limited to three years.

Your tasks

Your responsibility within this project will be the identification of parameters governing the degradation under load by artificial neural networks. In order to achieve this you will need to train and develop a neural network to correlate the results of experimental data obtained by other scientists and yourself in the project. This will allow us to evaluate the impact of different parameters on degradation and to provide input on further experimental work to expand the initial parameter space, thus fully describing the degradation process. You will work in close collaboration with a team tackling this problem by experimental and computational approaches to yield a mathematical model at the final stage.

Your profile

  • master’s degree or diploma in Physics, Data Science, Computational Material Science or a related discipline
  • strong analytical skills
  • knowledge in the areas of artificial intelligence, deep/machine learning
  • strong background in programming (e.g. Keras, TensorFlow, Matlab, C++ etc.)
  • background in the field of materials research with focus on electrochemistry and corrosion
  • experience with X-ray diffraction and X-ray imaging is an asset
  • team spirit, pro-active attitude, good communication skills and the ability to work efficiently in an interdisciplinary team has to be proven
  • proof of good written and spoken command of English is required (e.g. TOEFL, IELTS)
 

We offer you

  • multinational work environment with over 1,000 colleagues from more than 50 nations
  • extensive options of vocational training (i. a. expert seminars, language courses or leadership seminars)
  • flexible working hours and various models to ensure the compatibility of family and career
  • excellent infrastructure, including a scientific in-house library as well as modern work spaces
  • an appropriate salary related to the German public tariff (TV-AVH) plus the usual social benefits for the public employment sector

The promotion of equal rights is a matter of course for us. Severely disabled persons and those equaling severely disabled persons who are equally suitable for the position will be considered preferentially within the framework of legal requirements.




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Ab initio (from electronic structure) calculation of complex processes in materials