Digital Whole Plant Phenotyping Co Op

Job Description

Digital Whole Plant Phenotyping Co Op

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role are to:
  • Implement and optimize deep learning and machine learning algorithms, leveraging generative models for actionable insights and solutions.;
  • Evaluate needs, recommend experiments and projects, advocate for novel algorithmic pursuits, and inform strategic decisions.;
  • Utilize imaging and sensor technologies to collect and analyze phenotypic data, such as plant growth, plant development, biotic, and abiotic responses;
  • Communicate results in a timely and organized fashion to project team and key stakeholders through scientific reports and presentations;
  • Solve complex problems autonomously requiring original thinking, creativity, and deductive reasoning and the applicationof scientific principles on the design and interpretation of scientific experiments;
  • May be responsible for performing multiple experimental protocols under supervision;
  • Prioritize and coordinates work within a matrixed testing environment maintaining detailed record keeping and required documentation.;
  • Achieves commitment to safety and compliance, adhering to safety protocols and best practices.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:
  • Enrollment in a master's or Ph.D. program in Computer Science, Electrical Engineering, or an agricultural science program with a focus on computer vision or machine learning;
  • Solid foundation in Python programming and familiarity with deep learning frameworks such as TensorFlow or PyTorch;
  • Experience with model architectures and tools including ResNet, YOLO, R- CNN, DeepLab, GANs, VAEs and Transformers

Preferred Qualifications:
  • Previous experience with cloud platforms for model deployment, including AWS, Google Cloud, or Azure;
  • Experience using computer modelling techniques for plant development and imaged-based plant phenotyping, Implementation of machine learning and statistical models to identify or evaluate biotic and/or biotic stresses in plants.
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

Bayer is an E-Verify Employer. Location:United States : Missouri : Chesterfield Division:Crop Science Reference Code:827269 Contact Us Email:hrop_usa@bayer.com