Internship Agronomic Trial - Statistics (m/f/d)
Agriculture is all about balance. The balance that is crucial to everyone's existence - also applies to our Agricultural Solutions division. We connect innovative thinking with practical action to find the right balance for success - for farmers, agriculture and future generations. With seeds and traits, crop protection and digital solutions, we help farmers produce food more efficiently, protect the land and meet the needs of society. RESPONSIBILITIES
Be part of our Digital Farming Data team for 3 to 6 months, where we oversee and automatize the different agricultural trial activities within xarvio as well as provide farmers with modern sustainable and cost-saving agricultural management practices. In our group we cover a wide variety of data science tasks ranging from academic conceptual work to model deployment. You do not need to be an expert in all fields - we want to go give you the opportunity to apply your theoretical knowledge but also grow with us.
- You will support us conceptually evaluating our trial results and gain insights, which agricultural practices work best, under which circumstance such as optimizing the timing and intensity of crop production measures.
- Furthermore, you will research on and try out different methods in spatial statistics and evaluate them on real data sets.
- You will work in Cologne's Kranhaus, where you will develop, present as well as communicate your results in agile teams with stakeholders including the product, data and design teams.
- enrolled in computer science, statistics or another related field
- sound knowledge of spatial statistics, classical machine learning and design of experiments
- practical knowledge of using different data stores such as relational databases, data lakes and API as well as different data types like CSV, geospatial, raster and binary
- good coding practices in R or Python, vectorization, automation, documentation, packaging and source control (Git)
- excellent communication skills in English, self-motivated and interest in agricultural practices as well as sustainability topics
- From day one you will be part of the BASF family.
- You will get involved in challenging fields of activity and have the opportunity to work on exciting projects in an interdisciplinary environment.
- Depending on the location of the respective group company you will get to know BASF and participate in various workshops and guided tours.
- In this way you will make numerous interesting experiences and get a deep insight into the world´s leading chemical company. Information regarding internships: on.basf.com/internship
First information about our application process can be found here: http://on.basf.com/applicationprocess. At BASF, the chemistry is right.
Do you have any questions about the application process or the position? Please reach out to Karina Urich, Tel.: +49 30 2005-58528
xarvio Digital Farming Solutions powered by BASF is at the forefront of the digital transformation of agriculture optimizing crop production. xarvio offers digital products, based on a global leading crop model platform, which deliver independent field-zone-specific agronomic advice enabling farmers to produce their crops most efficiently and sustainable. The xarvio products SCOUTING, FIELD MANAGER and HEALTHY FIELDS are being used by farmers in more than 100 countries worldwide. Working at BASF Digital Farming GmbH is equally as innovative as our products: we have a global network and work with agile methodologies in a start-up atmosphere. Join our team! Learn more about xarvio at www.xarvio.com or visit any of our social media channels.
Because we are counting on innovative solutions, on sustainable actions, and on connected thinking. And on you. Become a part of our formula for success and develop the future with us - in a global team that embraces diversity and equal opportunities irrespective of gender, age, origin, sexual orientation, disability or belief. Please note that we do not return paper applications including folders. Please submit copies only and no original documents. Please upload the documents, summarized in a PDF if possible.
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