Position

Senior Scientist in Natural Sciences or Informat-ics/Computer Science for Statistical Data Analysis (Data Science)

Deadline

27/04/2018

Reference number

37/18-1.8

Salary

TVöD

Contract Term

temporary

Location


Richard-Willstätter-Straße 11
12489 Berlin

Division “Environmental Analysis”

To strengthen our team in Division “Environmental Analysis” in Berlin-Adlershof,
starting 01/07/2018, we are looking for a

Senior Scientist in Natural Sciences or Informat-ics/Computer Science for Statistical Data Analysis (Data Science)

Salary group 14 TVöD
Permanent contract
Full-time / suitable as part-time employment

Join us and be part of our motivated team.

Your responsibilities include:

- Collaboration within a new centre for mass spectrometry for organic environmental, food, materials and bioanalysis with responsibility for applied chemometrics, underpinning target, suspected target, and non-target strategies by high-resolution mass spectrometry (HRMS)
- Participation in the identification of contaminants, transformation products, metabolites and addtives by HRMS profiling of complex environmental, food, materials and biological samples as well as in HRMS-based fingerprinting in studies on authenticity, safety and security, and environmental sustainability of materials, products and food
- Development of innovative concepts for uni- and multivariate data analysis (Data Science) via establishment and application of software-based mathematical methods
- Build-up, maintenance and application of database tools for structure elucidation and prediction of unknown compounds, also underpinning our Open Data and digitisation strategies
- Interdisciplinary and international collaboration with experts in other fields
- Independent scientific publishing and presentation activities, acquisition and management of research projects as well as supervision of young academics

Your qualifications:

- An academic university degree in Natural Sciences or (Bio-)Informatics/Computer Science or a comparable discipline with an at least “good” result, a Ph.D. degree in one of these areas with predicate “very good” and follow-up experience as a postdoctoral researcher in a relevant research area
- Comprehensive knowledge and extensive practical experience in statistical data analysis, especially in dealing with HRMS data
- Profound experience in the employment of relevant software for multivariate data analysis/chemometrics and confident use of mass spectrometric data bases
- Proficiency in Analytical Sciences (instrumental analysis)
- Proven, international publication record (as self-responsible as possible) in relevant research fields
- Experience in proposal writing and acquisition of third-party funding
- Excellent command of the English language

We offer:

- Interdisciplinary research at the interface between politics, economics and society
- Work in national and international networks with universities, research institutes and industrial companies
- Outstanding facilities and infrastructure
- Equal opportunities

Your Application:

We welcome applications per email. Please send your application to the following address: bewerbung@bam.de by 27/04/2018, quoting the reference number 37/18-1.8. Please attach detailed application documents to the email as a summarised file in PDF format (max. 20 MB). Alternatively, you can also send your application by post, to:

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

Please note that all application documents will only be stored and processed for the selection procedure. Upon conclusion of the selection procedure, the documents will be deleted in compliance with regulations on data privacy.


The Head of Division 1.8 Environmental Analysis, Dr. habil. Rudolf J. Schneider, is happy to answer any specific questions you may have. Please get in touch via phone (+49 30 8104-1150) or e-mail (ru-dolf.schneider@bam.de).

BAM pursues equal opportunities. For this reason, we particularly welcome female applicants. Recognised disabled applicants with identical suitability will be selected preferentially.