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PhD Position in a Framework for Meta Data Analysis and Interactive Exploration of large FAIR data sets: A Plant Phenotyping example (f/m/d)
Forschungszentrum Jülich GmbH
As a member of the Helmholtz Association, Forschungszentrum Jülich makes an effective contribution to solving major challenges facing society in the fields of information, energy, and bioeconomy. It focuses on varied tasks in the area of research management and utilizes large, often unique, scientific infrastructure. Come and work with around 6,100 colleagues across a range of topics and disciplines at one of Europe's largest research centres.
The Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) provides an interdisciplinary environment for educating the next generation of data scientists in close contact to domain-specific knowledge and research. All three domains – life & medical sciences, earth sciences, and energy systems/materials – are characterized by the generation of huge heterogeneously structured data sets which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/
The Institute of Bio- and Geosciences (IBG) at the Forschungszentrum Jülich GmbH in Germany investigates important questions in the Bioeconomy. The department IBG-2 Plant Sciences, at the Forschungszentrum Jülich GmbH has a nationally and internationally leading role in quantitative assessment of structural and functional plant traits with non-invasive methods, plant genome analysis and using data management and machine learning. Within the IBG-2 our group focuses on the establishment of database resources for omics and phenotyping data, statistical and machine learning, the analysis of high throughput data and data visualization. In order to further improve these resources we are looking for a Doctoral Student to strengthen its international and interdisciplinary team.
We are offering a
PhD Position in a Framework for Meta Data Analysis and Interactive Exploration of large FAIR data sets: A Plant Phenotyping example
conceptualization, development and implementation of FAIR data standards
cooperating with the MIAPPE consortium as a proof of concept study
development of services for metadata analysis for data analysis using interactive visualization and (potentially web-based) deep learning and approximate data embedding approaches for data visualization and interpretation
MSc degree (or comparable) in computer science or in natural sciences with a strong background in software development and engineering
preferably, knowledge in browser based data visualization and mining tools such as DC, D3 and tensorflow.js and in numerical analysis
experience with plant data and metdata and corresponding acquisition/storage technologies as well as familiarity with R is a plus
excellent communication skills in English are mandatory: TOEFL or equivalent evidence of English skills
very positive university track record verified by bachelor and master study transcripts and two reference letters
you are convincing with your confident attitude and good communication skills
outstanding organizational skills and the ability to work independently
very good cooperation and communication skills and ability to work as part of a team in an international and interdisciplinary environment
outstanding scientific and technical infrastructure – ideal conditions for successfully completing a doctoral degree
unique HDS-LEE graduate school program
creative and international team that conducts research at the frontiers of science
themes ranging from computational neuroscience to simulation technology
chance of participating in (international) conferences
continuous scientific mentoring by your scientific advisor
doctoral degree conferred by RWTH Aachen University
further development of your personal strengths, e.g. via a comprehensive further training programme
a contract for the duration of 3 years
pay in line with 100 % of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund)
Forschungszentrum Jülich would like to employ more female staff in this area. We are therefore particularly interested in women's applications.
We also welcome applications from disabled persons.
We look forward to receiving your application, preferably via our
online recruitment system
career site, quoting the reference number 2019D-141.
Questions about the vacancy?
Contact us by mentioning the reference
number 2019D-141: firstname.lastname@example.org
Please note that for technical reasons
we cannot accept applications via
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