【简介】博士后招聘网整理分享“德国联邦材料测试与开发研究所2021年招聘博士后研究员”，浏览查询更多博士后招聘计划请访问博士后招聘网。

德国联邦材料测试与开发研究所2021年招聘博士后研究员

Postdoctoral Researcher (M/F/D) In The Field Of Engineering, Computer Science, Technical Software Development, Mathematics, Physics Or Data Engineering

BundesanstaltFürMaterialforschung Und –Prüfung

Description

Position

Postdoctoral Researcher (m/f/d) in the field of engineering, computer science, technical software development, mathematics, physics or data engineering

Deadline

12.12.2021

Reference number

317/21-7.7

Employment category

Full time /

Preferred start date

01.01.2022

Salary

E 13 TVöD

Contract Term

Limited / 31.12.2024

Location

Berlin Steglitz

Unter den Eichen 87 12205 Berlin

Division 7.7 - Modelling and Simulation

To strengthen our team in the division 7.7 “Modelling and Simulation” in Berlin-Steglitz, starting 01.01.2022, we are looking for a

Postdoctoral Researcher (m/f/d) in the field of engineering, computer science, technical software development, mathematics, physics or data engineering

Salary group 13 TVöD Temporary contract until 31.12.2024 Full-time / suitable as part-time employment

The BundesanstaltfürMaterialforschung und -prüfung (BAM) is a materials research organization in Germany. Our mission is to ensure safety in technology and chemistry. We perform research and testing in materials science, materials engineering and chemistry to improve the safety of products and processes. At BAM we do research that matters. Our work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and analytical sciences.

We are looking for talented people to join us.

Your responsibilities include:

The digitalization of engineering and material sciences holds versatile opportunities for the optimization of manufacturing processes and testing methods. In particular, machine learning methods show great potential here, e.g. in the prediction of material properties, the optimization of process parameters or as meta-models for complex physical models in the context of a digital twin. The application of machine learning techniques to safety- critical problems requires robust, explainable and generalizable models, which in particular can also provide estimators for the accuracy of the model prediction. Additionally, in the engineering domain, the dimensionality of the input data is relatively large, in addition to a relatively small number of data sets.

The goal is to develop procedures that allow statistical information in ML methods to be extracted for safety-critical problems, and in particular to obtain additional information from physical models (described by partial differential equations).

This project is a collaboration between the division 7.7 "Modeling and Simulation" and the unit S.3 "eScience". The position is embedded in the competence center Additive Manufacturing and is funded by the project Qi- Digital (Quality Infrastructure). The project is integrated in an international research environment and requires active networking with industry and research.

Your qualifications:

Completed scientific university studies (diploma or master's degree) in the field of engineering, computer science, technical software development, mathematics, physics or data engineering with a completed doctoral degree

Very good knowledge in the field of data science with machine learning tools and data mining methods (e.g. Tensorflow, PyTorch, Pandas, Scitkit- Learn)

Sound knowledge of statistics and probability theory (e.g. Bayesian inference)

Very good knowledge in at least one programming language (e.g. Python, C/C++, Julia)

Very good knowledge in the area of software development and corresponding frameworks

Basic knowledge in the area of finite element methods for the solution of differential equations (e.g. with the help of FEniCS)

Experience with version control systems (e.g. Git) is desirable

Proven publication activity in the relevant research area

Very good, precise and appropriate oral and written communication skills in German and English

Good communication and information behaviour, ability to work in a Team/ willingness to cooperate, flexibility, willingness and ability to make decisions as well as initiative/ commitment

We offer:

Interdisciplinary research at the interface of politics, economics and society

Work in national and international networks with universities, research institutes and industrial companies

Outstanding facilities and infrastructure

Flexible working hours and mobile working

Your application:

We welcome applications via the online application form by 12.12.2021. Alternatively, you can also send your application by post, quoting the reference number 317/21-7.7 to:

BundesanstaltfürMaterialforschung und -prüfungReferat Z.3 - Personal Unter den Eichen 87 12205 Berlin GERMANY www. bam.de

Dr. Unger will be glad to answer any specific questions you may have. Please get in touch via the telephone number +49 30 8104-3787 and/or by email to Joerg.Unger@bam.de.

BAM pursues the goal of professional equality between women and men. We therefore particularly welcome applications from women. In addition, BAM supports the integration of severely disabled persons and therefore especially welcomes their applications. With regard to the fulfilment of the job advertisement requirements, the application documents are examined individually. Recognised severely disabled persons will be given preferential consideration if they are equally suitable.

The advertised position requires a low level of physical aptitude.

Stay in touch with us:

150 Years BAM – Science with Impact. Celebrate with us: https: // 150.bam.de

Subscribe to our newsletter: https: // 150.bam.de/newsletter

Follow us on Twitter: https: // twitter.com/BAMResearch

Apply now!

Publications

Postdoctoral Researcher (m/f/d) in the field of engineering, computer science, technical software development, mathematics, physics or data engineering Kennziffer 317/21-7.7

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