德國(guó)材料研究與測(cè)試研究所2024年招聘博士后職位（材料科學(xué)中的機(jī)器學(xué)習(xí)）
德國(guó)聯(lián)邦材料研究和測(cè)試研究所，簡(jiǎn)稱BAM，是一個(gè)集材料研究、評(píng)估和咨詢的高級(jí)科學(xué)技術(shù)研究機(jī)構(gòu)，其與聯(lián)邦物理技術(shù)研究所（Physikalisch-TechnischeBundesanstalt，PTB），聯(lián)邦地球科學(xué)與自然資源研究所（Bundesanstaltfür Geowissenschaften und Rohstoffe，BGR）同隸屬于德國(guó)聯(lián)邦經(jīng)濟(jì)事務(wù)和氣候行動(dòng)部 [2]。BAM總部位于柏林Unterden eichen 87號(hào)，另有兩個(gè)分支機(jī)構(gòu)和一個(gè)大型試驗(yàn)場(chǎng)。該研究所始建于1871年，其前身組織為國(guó)家材料測(cè)試辦公室以及國(guó)家化學(xué)技術(shù)研究所，現(xiàn)有來自約50個(gè)國(guó)家或地區(qū)的約1600人在BAM工作。
Postdoctoral researcher in machine learning for materials science (m/f/d)
Bundesanstalt für Materialforschung und -prüfung (BAM)
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 23.10.2024. 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.
