Bayer

Internship in Machine Learning to Rank (all genders)

9 April 2024
Internship
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Deadline date:
£50000 - £100000 / year

Job Description

 

Where do you want to go? What do you want to achieve? How would you like to get involved? The choice is yours and we will support you on your way. At Bayer, multi-talents and specialists, visionaries and passionate people, thinkers and doers come together to feed the world, slow climate change and create healthier, more sustainable lives for all. This is the opportunity to start your career with a global leader committed to #HealthForAll #HungerForNone. Bring your ideas, skills and passion with you. Your career starts here.

 

Internship in Machine Learning to Rank (all genders) 

 

We are looking for you to join our team! You will support and learn about Learning to Rank extensions of an In-House Python package for Chemistry based Machine Learning and Explainable AI. With a potential option for Open Sourcing. Our team interacts with different stakeholders over different sites and is part of the Computational Life Science Indications Frankfurt group.

YOUR TASKS AND EDUCATIONAL OBJECTIVES

 

  • Design and realization of algorithms and software.
  • Get to know about Machine Learning, especially Learning to Rank approaches
  • Support the implementation of digital initiatives for AI in our company
  • Contribute to a positive team culture and work ethic based on Bayer LIFE (Leadership Integrity Flexibility Efficiency) values

 

WHO YOU ARE

Required:

  • Enrolled bachelor/master student (all genders) in Computer Science, Machine Learning, applied Mathematics, Physics, Bioinformatics, Cheminformatics or related fields
  • Familiarity with DevOps principles
  • Interested in implementing and advancing state-of-the-art methodologies for chemical compound screening
  • Excellent Python programming skills
  • Interested in building Python Package Development and Machine Learning skills
  • Fluent in English, both written and spoken

Desirable:

  • Experience in Scikit Learn 
  • Experience in Gradient Boosted Decision Trees (i.e., Catboost, Xgboost, LightGBM)
  • Basic knowledge in PyTorch and especially the Skorch library
  • Basic knowledge of chemistry and/or biology

 

WHY BAYER?

 

What counts for you, also counts for us! We believe in individual definitions of career, success, and work-life balance. You can expect a working environment in which you are welcomed, supported, and encouraged to bring your whole self to work. In addition to your work in dynamic and diverse teams, you can expect numerous benefits during your internship, such as:

  • A job ticket that allows you to flexibly and sustainably design your commute to work
  • The Corporate Benefits program, which entitles you as a Bayer employee to discounts from more than 150 brands
  • Professional development learning opportunities such as LinkedIn Learning and Education First

 

We offer this internship for a duration of 6 months (starting between May and July) in Frankfurt in a hybrid working model. We are looking forward to your application!

 

Ever feel burnt out by bureaucracy? Us too. That’s why we’re changing the way we work— for higher productivity, faster innovation, and better results. We call it Dynamic Shared Ownership (DSO). Learn more about what DSO will mean for you in your new role here https://www.bayer.com/en/strategy/strategy
Our Mission & Strategy: Through Dynamic Shared Ownership, we’re putting an end to the hierarchical model and putting more power in the hands of the innovators and creators at Bayer.

#LI-DE

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​

​​Division: ​               Crop Science​

Reference Code:  814431​

 

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