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Postdoctoral researcher in machine learning for materials science (m/f/d)

Employer
Bundesanstalt für Materialforschung und -prüfung (BAM)
Location
Berlin (DE)
Salary
TVöD EG14
Closing date
Nov 17, 2024
View more categoriesView less categories
Discipline
Life Sciences, Bioinformatics, Physical Sciences, Informatics
Position Type
Full Time
Job Type
Postdoc
Organization Type
Academia

To strengthen our team in the division "eScience" in Berlin‑Steglitz, starting as soon as possible, we are looking for a

Postdoctoral researcher in machine learning for materials science (m/f/d)

Salary group 14 TVöD
Temporary contract for 36 months
Full-time / suitable as part-time employment

The Bundesanstalt für Materialforschung 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.

Machine learning (ML) has become an influential tool in materials science, significantly enhancing the ability to design and discover new materials, predict material properties, and optimize material processing. Our mission in the eScience group is to develop new machine learning models for various applications in materials science.
Recently, we have created methods for analyzing SAXS measurements, interpreting electrochemical impedance spectroscopy (EIS) data, and predicting crystal stability. Additionally, we have contributed to the development of ML-based universal interatomic potentials, which are gaining popularity for simulating properties of large material structures. At BAM we have a tremendously broad research scope with many fascinating applications for ML methods. This is where your expertise comes in!
As a postdoctoral researcher you will push the boundaries of current ML applications in materials science. You will have the opportunity to develop your own research agenda and collaborate with other research groups to address challenging scientific questions.

As a member of the eScience group, you will be part of an interdisciplinary environment of creative minds. We offer a wide range of challenging tasks at the interface of computer science, data science, and materials research. Our team is renowned for its diversity and vibrant energy. This is your chance to work along international, young, innovative professionals who came together to shape the digitalization of materials research!

Your responsibilities include:

You will be responsible to develop and advance your own machine learning projects and to closely collaborate with materials scientists. In detail, this includes the following aspects:

  • Development of new machine learning models for applications in materials science
  • Implementation of machine learning models in pytorch and other relevant software libraries
  • Preparation of training data as well as development and selection of suitable features
  • Visualization and interpretation of results from predictions
  • Supervision of junior researchers
  • Communication of research results at scientific conferences and in peer-reviewed journals

Your qualifications:

  • Successfully completed university studies (diploma/master's degree) as well as a very good doctorate in computer science, technical software development, bioinformatics, mathematics, physics, data engineering or comparable
  • Very good knowledge of software libraries for data science (e.g., PyTorch, PyTorch-Geometric, Pandas, Scitkit-Learn)
  • Very good knowledge of the theory and practice of modern machine learning methods (e.g., invertible neural networks and graph neural networks)
  • Very good knowledge of at least one programming language (e.g., Python, Rust, Go)
  • Good knowledge of methods for visualizing complex data sets
  • Experience with version control systems (e.g., Git) is desirable
  • Experience with statistical methods is desirable
  • Knowledge of methods for processing and analyzing large amounts of data is desirable
  • Experience with data from the field of materials science or engineering or natural sciences is desirable
  • Excellent oral and written language skills/expressiveness in English
  • Excellent communication and interpersonal skills. Goal-oriented and structured way of working, with a strong willingness to cooperate and collaborate with others. Eager to learn and adopt, with strong conceptual, strategic and innovative thinking skills

We offer:

  • Interdisciplinary research at the interface of politics, economics and society
  • Engage in pioneering Interdisciplinary research at the intersection of politics, industry, and society
  • Work with leading national and international networks with universities, research institutions and industrial companies
  • Access to excellent equipment and infrastructure
  • Benefit from flexible working hours, mobile working, and strong work-life balance with 30 days of vacation and up to 12 compensatory days off per year
  • Personal and professional development
  • Benefit from an appreciative and inclusive atmosphere with a certified family-friendly working culture, regular feedback, and strong support for equality and the integration of severely disabled individuals

Your application:

We welcome applications via the online application form by 20.11.2024. Alternatively, you can also send your application by post, quoting the reference number 221/24-VP.1 to:

Bundesanstalt für Materialforschung und -prüfung
Referat Z.3 – Personal
Unter den Eichen 87
12205 Berlin
GERMANY
www.bam.de

Dr. Benner will be glad to answer any specific questions you may have. Please get in touch via the telephone number +49 30 8104‑3647 and/or by email to Philipp.Benner@bam.de.

BAM promotes professional equality between women and men. We therefore particularly welcome applications from women. At the same time, we strive to reflect social diversity. Every application is therefore welcome, regardless of gender, cultural or social background, religion, ideology or sexual identity.

In addition, BAM has set itself the goal of promoting the professional participation of people with severe disabilities. The fulfillment of the job requirements is considered on an individual basis. Severely disabled persons or persons of equal status will be given preferential consideration if they are equally qualified.

The advertised position requires a low level of physical aptitude.

BAM actively supports the compatibility of work and family and has been certified as a family- and life-phase-conscious employer by the "audit berufundfamilie" since 2015.

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