80%-100%, Zurich, fixed-term
The group of crop science develops new phenotyping tools and analysis protocols for plant breeding and agroecosystem research. It operates the field phenotyping platform (FIP ) and the phenofly drone platform.
The group of crop science participates in several international research programs in the framework of EMPHASIS , aiming to develop and implement a pan-European plant phenotyping infrastructure. Within this framework, a new project will be launched in 2023 (EMPHASIS/PHENET; HORIZON-INFRA-2022) which will equip a European crop and ecosystems research infrastructure with innovative services and sensing concepts. PHENET will capitalize on big data derived from a common sensing and phenotyping network across Europe. We will participate in the use-case "wheat" of PHENET and seek for a person with a strong interest in crop physiology and physiological breeding.
The position includes a wide range of techniques like testing innovative scientific instrumentation, deep learning and image processing, crop modelling and advanced field phenotyping. You are expected to be familiar with at least one of these domains. The position is limited to two years with the possibility of an extension.
As a crop phenotyping data scientist, you will help develop tools and methods in high throughput crop phenotyping and envirotyping. This includes training deep learning models for advanced feature extraction from images and developing model-assisted wheat phenotyping to predict genotype performance and adaptation to future environmental conditions.
As data scientist and coordinator within PHENET, you are responsible for the following domains: coordinating data exchange with other labs within PHENET; extending the FIP platform with IoT-based field sensors and edge devices; interacting with the PHENET data modelling team to leverage AI methods and process-based models. The latter includes the integration of dense, multi-location (Switzerland, France, Portugal) information about genotypes, environments, and management practices into the GxExM continuum.
As a team member of the crop science group, you will participate in wheat phenotyping experiments in the FIP and at other PHENET field sites. You will participate in teaching activities and the supervision of PhD and master students.
- You have a PhD in plant breeding, crop phenotyping, image processing, crop modelling, quantitative genetics or a related field.
- This is a position demanding an intensive interaction between persons with different backgrounds in the domain of crop phenotyping.
- You should be an excellent team player and communicator.
- This position requires a profound knowledge of data management and statistical modelling.
- You must be fluent in either R (Tidyverse) or Python.
- Knowledge of mixed model software (ASREML) and/or crop models (e.g. APSIM or Sirius wheat) is a plus.
- You have demonstrated your writing skills by means of first-authored, peer-reviewed publications.
- ETH offers excellent training opportunities which are accessible to our postdocs.
- Our working language is English.
- The group crop science offers flexible office hours, the possibility of part-time work and home office.
- We offer a diverse working environment and diverse workplaces: you can choose the vibrant heart of the city of Zurich (LFW building ) or our quiet experimental field station in Eschikon with excellent access to pubic transportation.
- We are a diverse and enthusiastic team that loves interacting with different communities including scientists in robotics, computer science, molecular breeding and remote sensing.
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Curious? So are we.
We look forward to receiving your online application with the following documents:
A half-page motivation letter
Your publication list, including ORDIC authors identifier
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about the Institute of Agricultural Sciences and the group of crop science can be found on our websites at https://www.ias.ethz.ch/ and https://kp.ethz.ch/ , respectively. Questions regarding the position should be directed to Dr. Andreas Hund, firstname.lastname@example.org (no applications).
About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.
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