Research Engineer in Computer Vision for Life Sciences (m/f)
Your tasks and responsibilities
- Development and implementation of innovative, state-of-the-art tools and technologies in digital imaging to support the Pharmaceuticals, Consumer Health and Crop Science divisions in drug discovery and development, phenotyping, digital agriculture and digital health
- Development of creative and innovative ideas to increase Bayer's competitive advantage and innovative edge in this field
- Establishing a dynamic, flexible, transparent, results-oriented and innovative working atmosphere
- Maintaining existing and developing new value-adding internal and external cooperation networks
Who you are
- Master of Science or PhD in Computer Science, Computer Vision, Electrical Engineering, (Bio-)Informatics, (Bio-)Physics (IT), or a related discipline
- Professional experience in digital image processing, preferably in the field of life sciences
- Profound experience with programming/scripting in Python and C/C++, image processing libraries (OpenCV), Deep Learning Frameworks (TensorFlow, Caffe, PyTorch etc.) and interface programming
- Excellent knowledge in the fields of augmented reality, artificial intelligence, machine learning, deep learning, cloud computing as well as practical experience in handling large volumes of data
- Flexibility, self-initiative and delight to work in a highly interdisciplinary environment.
- Systematic, structured and responsible approach to your work
- Excellent English skills, both written and spoken
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. Bayer begrüßt Bewerbungen aller Menschen ungeachtet von ethnischer Herkunft, nationaler Herkunft, Geschlecht, Alter, körperlichen Merkmalen, sozialer Herkunft, Behinderung, Mitgliedschaft in einer Gewerkschaft, Religion, Familienstand, Schwangerschaft, sexueller Orientierung, Geschlechtsidentität oder einem anderen sachfremden Kriterium nach geltendem Recht. Wir bekennen uns zu dem Grundsatz, alle Bewerberinnen und Bewerber fair zu behandeln und Benachteiligungen zu vermeiden.
Reference Code: 12752