At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.
Automated Greenhouse Expert - Phenotyping & Data Analysis (all genders)
YOUR TASKS AND RESPONSIBILITIESYou will implement ad-hoc data analyses, including models for image analysisYou will drive the application of new sensors and methods to improve the quality of experiments, sensor-based plant phenotyping, and data analysisYou will support the practical execution/analysis of greenhouse experiments in an automated environmentTogether with the team, you will drive the development of automation and digitalization to increase the efficiency and quality of experiments and dataYou will collaborate with various technical disciplines, customers, and suppliers to ensure successful daily operations
Special Tasks - Phenotyping & Data AnalysisExpert (all genders) in sensor-based plant phenotypingExpert (all genders) in automated image analysis, machine learning/deep learning, and data visualizationExperience in applying sensor technology for plant phenotyping (plant physiology is a plus)YOUR QUALIFICATIONSA completed degree in computer vision, plant sciences, agriculture, or similar, with a Master's, Bachelor's with initial experience, or technical training with several years of experience in programming (Python, R)Experience with computer and/or software systems used in scientific image and data analysis, with the ability to quickly learn new software programs and tools; solid knowledge in deep learning and machine learning is an advantageHands-on mentality with technical skills and interest in practical work in the greenhouse (experience with greenhouse automation is a plus)Data analysis, including statistical analysis and data visualizationExcellent organizational skills, strong problem-solving abilities, and effective implementation of operational strategies with a "can-do" attitudeProven ability to handle ambiguity and a high degree of complexity very well, with a high level of self-motivation, self-responsibility, proactivity, and the ability to make and drive decisionsHigh level of social competence, strong communication skills, and dealing with stakeholders as part of a team and cross-functionally in a dynamic, highly cooperative work environmentWillingness to occasionally work on weekends to ensure the automation flowFluent German and English skills, both spoken and written, complete your profile
We are excited about your talent and passion for this position. Attracting the right talent is important to us. We would be happy to work with you to identify and create the career and development opportunities you are looking for - also in part- time. And if you don't meet all the requirements, we still look
forward to receiving your application. We are all constantly learning!
Be you. Be Bayer
YOUR APPLICATION
This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health, feeding growing populations and slowing the rate of climate change. You have a voice, ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer.
Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.
Location: Frankfurt a.M.
Division: Crop Science
Reference Code: 815642