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an engineer or an intern (50%-100%) for: Data-driven and physics-based optimization of postharvest supply chains from farm to fork

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an engineer or an intern (50%-100%) for: Data-driven and physics-based optimization of postharvest supply chains from farm to fork

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an engineer or an intern (50%-100%) for: Data-driven and physics-based optimization of postharvest supply chains from farm to fork

Application Deadline: 11/04/2020 08:40 - Europe/Brussels

Contact Details

Where to send your application.

Company Empa
  • WEBSITE https://academicpositions.com/ad/empa/2020/an-engineer-or-an-intern-50-100-fo...
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    Hiring/Funding Organisation/Institute

  • ORGANISATION/COMPANY Empa
  • ORGANISATION TYPE Higher Education Institute
  • WEBSITE http://www.empa.ch/plugin/template/empa/3/*/---/l=2
  • COUNTRY Switzerland
  • CITY Dübendorf
  • POSTAL CODE Ueberlandstrasse 129
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  • ORGANISATION/COMPANY Empa
  • RESEARCH FIELD Agricultural sciences › Other Computer science › Database management Computer science › Other Economics › Other Engineering › Other Mathematics › Statistics Technology › Environmental technology
  • RESEARCHER PROFILE First Stage Researcher (R1)
  • APPLICATION DEADLINE 11/04/2020 08:40 - Europe/Brussels
  • LOCATION Switzerland › Dübendorf
  • TYPE OF CONTRACT Temporary
  • JOB STATUS Full-time
  • HOURS PER WEEK 38
  • Empa - the place where innovation starts

    Empa is the research institute for materials science and technology of the ETH Domain and conducts cutting-edge research for the benefit of industry and the well-being of society.

    Empa’s Laboratory of Biomimetic Membranes and Textiles is looking for

    an engineer or an intern (50%-100%) for: Data-driven and physics-based optimization of postharvest supply chains from farm to fork

    Our laboratory . Empa’s Laboratory of Biomimetic Membranes and Textilesaims to develop materials and systems for the protection of the human body and its health. The products developed in collaboration with industry are used in the fields of occupational safety, sport, medical applications, and health-tech.

    Background Optimizing postharvest cold chains of fruits and vegetables across all unit operations is of key importance to maintain fresh food quality and to reduce food losses. Temperature and the gas composition in the air are affecting decay and food quality, so they need to be controlled during precooling, refrigerated transport, and cold storage. By optimizing these environmental parameters, shelf life can be maximized. Currently, extensive monitoring is performed on the environmental conditions in food supply chains (air temperature and humidity). However, often, such sensing only covers a part of the cold chain and not the entire journey from farm to fork. Taking into account the entire journey is essential to quantify how the fresh-food quality evolves, and what the final quality and shelf life are that the retailers, and thus the consumer, receive. In addition, only simplified analyses are performed on these huge datasets. This makes that there is most probably a lot of unexplored information in the data. 

    Objective . The key objective is to better use this sensor data to identify when and where the quality loss occurs, and how commercial cold chains can be improved, to reduce food loss. To this end, data-driven and physics-based modeling are used, among others by integration into digital twins. This project is performed in collaboration with a Swiss retailer. In this project, you will be able to improve future supply chains of fruits and vegetables in order to reduce the environmental impact of the food we consume.

    Your tasks:

  • Organize experiments in commercial cold chains, process the measured sensor data statistically, reformat data in databases, and analyze data for variability.

  • Analyze the data with statistical techniques (e.g. PCA, Monte Carlo) to identify critical problem locations in the cold chain. As a next step, more advanced data-driven techniques, such as machine learning, can be explored.

  • Use this data to build up and use physics-based and/or data-driven digital twins

  • Propose solutions to improve the shelf life and reduce food losses and test these solutions in the field by full-scale trails.

  • Support other physics-based and data-driven projects in the lab and set up a framework for quality assurance in modeling & simulation

  • Support in the organization of modeling and simulation events.

  • The work will be performed at the facilities of Empa (St. Gallen). Regular visits to the facilities of the Swiss retailer company are likely to be required.

    Your profile:

  • Completed Master`s degree in engineering, food science, physics or data science at a university or university of applied sciences. For interns, an ongoing Master's degree can also be considered.
  • Knowledge in one or more of the following disciplines: convective heat and mass transfer, food cold chains, hygrothermal measurements, data science.
  • Experience in statistical data analysis (such as R, ANOVA). Knowledge of ML techniques is considered advantageous.
  • Experience in physics-based modeling, such as finite element modeling and computational fluid dynamics.
  • Excellent communication skills and fluency in English (both written and oral) are mandatory. Knowledge of German is considered very advantageous.
  • Administration . A project duration of 1 year is envisaged to carry out the above research tasks. However, a further extension is possible but needs to be discussed, depending on the qualifications of the candidate and the workload percentage. Internships are also expected to stay for 1 year. The project is supported by Empa under the supervision of Thijs Defraeye. The desired starting date is 1st of June 2020 or upon mutual agreement. A workload of 50%-100% is acceptable and can be negotiated.

    For further information about the position please contact Thijs Defraeye Thijs.defraeye@empa.ch and visit our websites www.empa.ch/web/s401 and Empa-Video

    We look forward to receiving your online application, including all following documents: (1) a letter of motivation, (2) CV including publications and presentations, (3) diplomas with transcripts, and (4) contact details of two referees. Incomplete applications will not be considered. Please upload the requested documents through our webpage. Applications via email will not be considered.

    Empa, Esther Zürcher, Human Resources, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland.

    Additional Information

    Web site for additional job details

    https://academicpositions.com/

    Requirements

    Required Research Experiences

  • RESEARCH FIELD Agricultural sciences
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Computer science
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Computer science
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Economics
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Engineering
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Mathematics
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • RESEARCH FIELD Technology
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • Map Information

    +-Leaflet | Map data Google Job Work Location Personal Assistance locationsGet More Personal Assistance Work location(s) 1 position(s) available at Empa Switzerland Dübendorf CH-8600 Ueberlandstrasse 129

    EURAXESS offer ID: 504044
    Posting organisation offer ID: 141953

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    Veröffentlicht am

    08-02-2021

    Extra Informationen

    Status
    Inaktiv
    Ausbildungsniveau
    Andere
    Standort
    Landesweit
    Arbeitsstunden pro Woche
    8 - 40
    Jobart
    Nebenjob/Wochenendjob
    Tätigkeitsbereich
    Marketing / Kommunikation / PR / Werbung
    Führerschein erforderlich?
    Nein
    Auto erforderlich?
    Nein
    Motivationsschreiben erforderlich?
    Nein
    Sprachkenntnisse
    Deutsch

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