Postdoctoral Position (m/f) Data analysis for Biomaterials

code no. 2018/WB 8
The place of employment is Geesthacht, Germany. Research at HZG in the field of "Metallic Biomaterials" focusses on the development of biodegradable Mg-based alloys and implants by the optimization of mechanical, biological and degradation properties for specific applications. To this end, it is crucial to understand the mechanisms governing the interactions between microstructure, mechanical properties, biology and degradation. In the long run, such understanding will enable the manufacturing of implants tailored to the specific needs of individual patients. To achieve this we plan to analyse large amounts of data from different experimental setups by machine learning in order to identify key factors which determine the implant performance.

This postdoctoral position is a full time position, fixed term 3 years, starting date as soon as possible.

Project description:

You will be responsible for the development and implementation of a data base containing experimental and simulation data from various sources (e.g. materials data including microstructure and mechanical properties, processing data from different fabrications steps, data on degradation, imaging data from MRI, X-ray, synchrotron, optical measurement, SEM, TEM and other sources as well as biological and medical data). The data base has to store the data in a way that allows easy access from different simulation and modelling tools as well as data analysis tools. As a proof of concept and to verify the usability of this data base for specific questions machine learning algorithms should be employed.
You will work in close cooperation with other post-docs responsible for the development of a computational multi-physics model of chemo-mechanical degradation of biomedical magnesium implants and related phenomena as well as imaging experts and scientist modelling the tissue reaction with respect to Mg degradation. In detail, you will be responsible for:

• development of the fundamental concept of the data base considering especially the very different data sources and identifying their common features in order to enable consistent and easy access to and evaluation of data
• implementation of the data base
• generation of a testing concept with artificial correlated data
• collection of suitable existing data and step-wise feeding of the data base under continuous testing
• application of machine learning algorithms to identify simple correlations between material properties and cellular response
• if needed, initiation of specific experiments to gain missing data

Requirements:

• university degree (MSc, Diploma or equivalent) and PhD in data / computer science, natural sciences or engineering
• strong analytical skills and sound theoretical background
• excellent programming skills in Python
• experience in implementation of data bases and with at least one data base language (e.g., SQL, MySQL) is appreciated
• experience with machine learning / deep learning is appreciated
• background knowledge in the field of metallic (bio)materials, in particular magnesium for biomedical applications, is appreciated
• team spirit, excellent communication and organization skills, fluent English

We offer:

• multinational work environment with over 950 colleagues from more than 50 nations
• extensive options of vocational training (for instance, 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
• remuneration according to the standards of the collective wage agreement TV-AVH including further social benefits

You will work in a team of several computational scientists and experimentalists who can provide data along the full chain from material design up to in vivo data.