Open Positions

Open positions at Fraunhofer IVV

Open positions at FAU Erlangen

PhD Positions

2 PhD positions in the EU Horizon 2020 Marie Skłodowska-Curie Project C-PlaNeT:
ESR 08: Odour characterization, monitoring, control and removal from recycled plastics.
ESR 15: Recycling of polymers from collected ocean/beach plastics.

General Information:
Applications are invited for 2 PhD positions (“Early Stage Researchers”) to be funded by the Marie-Skłodowska-Curie Innovative Training Network “C-PlaNeT – Circular Plastics Network for Training” within the Horizon 2020 Programme of the European Commission. C-PlaNeT is a consortium of high-profile universities, research institutions and companies located in Belgium, Germany, the Netherlands, Austria, United Kingdom, Switzerland, Denmark and Greece.
Europe needs this training network. Bringing plastics into the circular economy is one of the great challenges of our age. C-PlaNeT lays the foundations for a New Plastics Economy through a European Joint Doctoral Programme that trains 15 Early Stage Researchers (ESRs) to become part of a new generation of scientists, engineers and policy makers for the EU’s circular economy, including the design, processing, use and reuse of plastics. Each ESR, developing his/her research skills together with a supervisor and co-promoter, represents a piece of the jigsaw, at the same time benefiting from being part of a project team with 14 other ESRs and their supervisors covering other parts of the life cycle, challenging each other in terms of lifecycle thinking and a much more sustainable future for plastics.

All information can be found on the website: . Applicants need to apply via e-mail (
Application deadline: 30.04.2020

The successful candidates will receive an attractive salary in accordance with the Marie-Skłodowska-Curie Action regulations for Early Stage Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). The salary includes a living allowance, a mobility allowance and a family allowance (if married). The guaranteed PhD funding is for 36 months (i.e. EC funding, additional funding is possible, depending on the local Supervisor, and in accordance with the regular PhD time in the country of origin). In addition to their individual scientific projects, all fellows will benefit from further continuing education, which includes internships and secondments, a variety of training modules as well as transferable skills courses and active participation in workshops and conferences.
For further information, please contact the central office (

ESR 8 – Odour characterization, monitoring, control and removal from recycled plastics
Start date: 01.06.2020; duration: 36 months

The candidate will optimize and apply chemo-analytical methods based on the extraction of volatile and odorous compounds and subsequent analysis by gas chromatography-mass spectrometry coupled to olfactometry to identify marker compounds contributing to the odor of recycled plastics, and elucidate their formation pathways and origin. Modifications of the recycling process will be developed and applied to evaluate their usefulness in reducing the odor load of the materials, with a focus on washing processes. Sensor technologies will be selected and evaluated with regard to their use for in-process quality control to enable application-oriented recycling processes

The objective is to characterize the causative odour-active constituents in recycled plastics by using smell-guided chemo-analytical methods. The knowledge of the molecular underpinnings of the respective smells will be used for guiding odour-minimization technologies. Another focus will be on the identification and adaptation of sensor strategies for in-line detection and monitoring of odour emissions in recycling processes

Planned Secondments: UG to perform washing tests on a semi-continuous friction washer, testing different washing media (cold/hot water, caustic, detergents, solvents, etc.), including process design for recovery of washing media (M18-M24); Fraunhofer IVV to select and test sensor technologies for monitoring odour emissions (M36-M38)

ESR 15 – Recycling of polymers from collected ocean/beach plastics
Start date: 01.06.2020; duration: 36 months

Marine/beach plastics will be characterized with regard to their overall chemical composition. Current recycling technologies will be tested and adapted to recover selected target polymers. These will be tested for their purity, physical/mechanical properties and presence of contaminants and volatiles using a range of physical/chemical methods including gas chromatography-mass spectrometry and high performance liquid chromatography-mass spectrometry

The objective is to recover high-quality polymers from marine and/or beach plastics. Therefore, the candidate will identify current and suitable collection systems for beach and/or marine plastics and organize samples. In a next step these materials will be characterized in depth. Using innovative recycling technologies, these infeed materials will be cleaned and used as a source of secondary polymers. These are extracted from the bulk inputs and cleaned thoroughly using – amongst other processes – solvent-based purification and enrichment processes. Additionally chemical recycling will be evaluated, in particular because mechanical recycling might prove to be infeasible

Plannded Secondments: UG for thermochemical recycling of non-target polymers identified and separated from marine/beach plastics (M36-M41). OWS to evaluate degradation of plastics in marine environment (M13); Fraunhofer IVV for the use of Creasolv Technology (M8-12,18-20)


In our working group, we offer a wide range of topics for Bachelor, master, diploma and state exam theses for students from the fields of Chemistry (especially Food Chemistry, Analytical Chemistry and Organic Chemistry), Molecular Sciences, Food Technologies, Nutrition Sciences and related programs. In general, we offer theses in the following areas.


Synthesis and Characterization of Odor Active Substances, Examination of Structure-Odor Relations

The aim of the work is the synthesis of structurally related volatile compounds potentially included as odorants in food, plant materials or even synthetic materials (such as plastics). The synthesized target components are characterized by analytical parameters such as mass spectra, NMR spectra, retention indices. In addition, their odor properties are recorded and possible structure-odor relationships identified. Furthermore, the human sensory evaluation of the compounds and the determination of odor thresholds are performed.

Applicants need in-depth knowledge of the synthesis of organic compounds and must have sufficient laboratory experience to ensure safe and independent work. Experience with sensory examinations and analytical methods, in particular gas chromatography, as well as MS and NMR would be an advantage.

For queries and applications, please contact

Nadine Goldenstein,


Qualitative and Quantitative Analysis of Odorous Substances

The aim of the work is the analytical characterization of odor-active substances, which are potentially important in food, plant materials or synthetic materials such as plastics for the aroma or the smell of the product. The target components are identified and quantified in the respective materials by analytical methods, in particular gas chromatography olfactometry or GC-MS. In order to be able to quantify the substances in the respective materials by means of GC-MS, the synthesis of stable isotope-labeled analogues of the odor-active substances will – if necessary – also be the subject of the work.

Applicants must be able to work independently and safely in chemical laboratories and must have in-depth knowledge of the analysis of organic, in particular volatile compounds.  Initial experiences with gas chromatographic analyses as well as experiences in sensory examinations and other analytical methods, in particular MS and NMR, is preferable.

For queries and applications, please contact

Nadine Goldenstein,


Current Projects

Abschluss-/Masterarbeit zum Thema: „Vorhersage sensorischer Eigenschaften von Materialien“

Die sensorischen Eigenschaften von Materialien, insbesondere der Geruch, sind sowohl wissenschaftlich als auch wirtschaftlich von entscheidendem Wert. Mit gängigen experimentell-chemischen und computer-chemischen Methoden lassen sich die sensorischen Eigenschaften allerdings nicht anhand der molekularen Struktur vorhersagen. Das Fraunhofer IVV entwickelt zusammen mit der FAU Erlangen Methoden des maschinellen Lernens (ML) und der künstlichen Intelligenz (KI) zur Vorhersage der sensorischen Eigenschaften von Molekülen. Dazu müssen spezifische ML/KI-Methoden implementiert und qualitativ hochwertige Datensätze molekularer Eigenschaften erstellt werden.

Diese Arbeit ist angesiedelt an der Schnittstelle zwischen chemisch-experimentellem Arbeiten im Labor und datenwissenschaftlichem Arbeiten mit modernster IT. Wichtig: Die IT-Fähigkeiten müssen Sie nicht mitbringen, sondern können Sie on the job lernen. Ziel dieser Arbeit ist die Erstellung qualitativ hochwertiger Datensätze zur algorithmischen Auswertung durch KI-Methoden, die Weiterentwicklung der Algorithmen, und die Validierung algorithmisch getroffener Aussagen durch experimentelle Synthetik und Analytik.

Ihre Aufgaben können umfassen:

  • Chemische und sensorische Analytik
  • Planung und Durchführung synthetischer Arbeiten
  • Erstellung qualitativ hochwertiger Datensätze
  • Anwendung von ML/KI-Methoden auf molekulare Datensätze
  • Weiterentwicklung von Methoden
  • Bewertung, Validierung und Dokumentation der Ergebnisse

Was Sie mitbringen:

  • Sie studieren einen naturwissenschaftlichen oder technischen Studiengang, insbesondere Chemie, Lebensmittelchemie, Mathematik, Informatik oder verwandte Fächer
  • Sie müssen keine Kenntnisse in Programmierung, ML/KI oder Data Science mitbringen, dann aber die zwingende Bereitschaft, sich in diese Themen einzuarbeiten
  • Programmierkenntnisse (idealerweise Python) und Kenntnisse in maschinellem Lernen sind erwünscht und vorteilhaft
  • Sehr gute Deutsch- oder Englischkenntnisse
  • Hohes Maß an Selbstständigkeit, Eigeninitiative und eine hohe Bereitschaft, sich in neue und komplexe Sachverhalte einzuarbeiten
  • Team- und Kommunikationsfähigkeit

Was Sie erwarten können:

  • Sie erhalten fundierte Kenntnisse und Praxiserfahrung in der Anwendung und Entwicklung aktueller Methoden der Data Science und der künstlichen Intelligenz
  • Sie arbeiten zugleich klassisch experimentell und modern datenwissenschaftlich in einem einmaligen Umfeld mit exzellenter Ausstattung an Labor- und IT-Technik
  • Sie können ihre eigenen Ideen einbringen und umsetzen
  • Wir arbeiten zielorientiert mit agilen Methoden



Fragen zu dieser Position beantwortet Ihnen gerne:

Dr. Thilo Bauer

Computer-Chemie-Centrum der FAU

Nägelsbachstr. 25

91052 Erlangen