Wo möchtest du hin? Was möchtest du erreichen? Wie möchtest du dich einbringen? Du hast die Wahl und wir unterstützen dich auf deinem Weg. Bei Bayer kommen Multitalente und Spezialist*innen, Visionäre und leidenschaftliche Menschen, Denker*innen und Macher*innen zusammen, um die Welt zu ernähren, den Klimawandel zu verlangsamen und gesündere, nachhaltigere Leben für alle zu schaffen. Dies ist die Gelegenheit, deine Karriere bei einem weltweit führenden Konzern zu starten, der sich für #HealthForAll #HungerForNone einsetzt. Bringe deine Ideen, dein Können und deine Leidenschaft mit. Deine Karriere beginnt hier.

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

DEINE BEWERBUNG

Dies ist deine Chance, dich mit uns gemeinsam den größten globalen Herausforderungen unserer Zeit zu stellen: die Gesundheit der Menschen zu erhalten, die wachsende Weltbevölkerung zu ernähren und den Klimawandel zu verlangsamen. Du hast eine Stimme, Ideen und Perspektiven, die wir hören möchten. Denn unser Erfolg beginnt mit dir. Sei dabei. Sei Bayer. 

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 Bewerber*innen fair zu behandeln und Benachteiligungen zu vermeiden. 
 

Standort:           ​​ ​   Frankfurt​

​​Division: ​               Crop Science​

Referenzcode:      814431​