Data Scientist (m/f/d) for Materials Science

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

Data Scientist (m/f/d) for Materials Science

Salary group 14 TVöD
Permanent contract
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 improving the ability to develop and discover new materials, predict material properties, and optimize material processing. Our task in the eScience group is to develop new machine learning models for various applications in materials science. At BAM we have an enormously broad research spectrum with many fascinating applications for ML methods. This is where your expertise comes into play!

In the eScience group, you will be centrally responsible for ensuring that machine learning methods are widely applied. You will have the opportunity to develop your own research agenda and collaborate with other research groups to tackle challenging scientific questions.

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

We are looking for talented people to join us.

Your responsibilities include:

You will be responsible for developing and advancing your own machine learning projects and work closely with materials scientists. In detail, this includes the following aspects:

• Processing and analysis of data from various subject areas (materials science, energy, infrastructure, environment and analytical sciences) generated by BAM's specialist departments
• Application of modern methods of statistics and machine learning to analyze data sets and to link experiments with simulations
• Application of specific methods for the visualization of large amounts of data and research results
• Advice on the methodology of data analysis and statistics, accompanying processing of research-driven questions, interpretation of results and derivation of recommendations for action
• Conception and development of semi-automated routines for the consolidation and systematic processing of subject-specific primary data and metadata
• Implementation of analysis methods for continuous quality assurance of complex, heterogeneous data sets at the interface to research data management systems
• Providing impetus for internal and externally funded research projects with a focus on data science
• Positioning BAM as a departmental research institution through participation in national and international networks
• Supervision of doctoral candidates and students

Your qualifications:

• Successful scientific university degree specialising in computer science, technical software development, bioinformatics, mathematics, physics, data engineering or comparable and a very good PhD
• Very good knowledge of data science with machine learning tools and data mining methods (e.g. PyTorch, Tensorflow, Pandas, Scitit‑Learn)
• Very good knowledge of at least one programming language (e.g. Python, Rust, C++)
• Good knowledge of methods for visualizing complex data sets
• Experience in the supervision of junior researchers
• Excellent oral and written language skills/​expressiveness in English
• Experience with version control systems (e.g. Git) is desirable
• Experience with statistical methods and software (e.g. GNU‑R) is desirable
• Experience with data from the field of materials science or engineering or natural sciences is desirable
• 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:

• 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. We particularly welcome applications from women

Your application:

We welcome applications via the online application form by10.10.2024. Alternatively, you can also send your application by post, quoting the reference number216/24-VP.1to:

Bundesanstalt für Materialforschung und ‑prüfung
Referat Z.3 - Personal
Unter den Eichen 87
12205Berlin
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 +49308104‑3647 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.