HIT Discovery Cheminformatician DELs (all genders)

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Bayer is seeking a HIT Discovery Cheminformatician DELs for the DNA-Encoded Library program in Wuppertal Germany to drive the early research portfolio by identifying chemical entry points, enabling lead finding with cutting edge cheminformatics and ML, building workflows for DEL screening data and guiding hit to lead decisions in collaboration with experimental and computational teams. The role requires a PhD in Biostatistics, Chemoinformatics or Computational Sciences or a BS/MS with substantial industry experience, fluent English with basic German, strong Python and RDKit skills, and experience with ML for SAR/QSAR as well as Git, CI/CD and cloud platforms. Salary ranges 88,900 to 108,000 EUR plus benefits, with hybrid options and dedicated development programs. To apply, tailor your CV to show measurable impact in DEL informatics, data stewardship, cross functional collaboration and data driven decision making; highlight interdisciplinary projects and clear communication.

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.

HIT Discovery Cheminformatician DELs (all genders) 

YOUR TASKS AND RESPONSIBILITIES

• As drug hunter, drive the Bayer early research portfolio by identifying chemical entry points to drug discovery programs, actively shaping project team decisions
• Enable lead finding campaigns using cutting-edge cheminformatics and statistical approaches to guide data-driven decision-making 
• Build analysis workflows for DNA-encoded library screening data 
• Perform cheminformatic analysis of large-scale screening data (small molecules and peptides), building SAR models and guiding data-driven hit-to-lead processes
• Partner with experimental and computational scientists within Drug Discovery Sciences organization and  Data Science & AI to advance computational analysis tools for hit discovery
• Manage data stewardship of DNA-encoded library screening results to foster FAIR data principles (findability, accessibility, interoperability, and reusability) 

WHO YOU ARE

• PhD degree in Biostatistics, Chemoinformatics, Computational Sciences or related disciplines with several years of experience, or a BS/MS with extensive relevant industry research experience
• Basic chemical or biological understanding relevant for drug discovery  
• Previous experience in application of DNA-encoded library informatics and machine learning methods for hit discovery is a plus, including the application of deep‑learning and neural‑network approaches to support the identification of relevant chemical matter
• Advanced proficiency in Python, cheminformatics toolkits such as RDKit, data-analysis and workflow platforms such as Spotfire or Pipeline Pilot, and applied machine learning for SAR/QSAR modelling, hit prioritization, and chemical-space analysis using frameworks such as scikit-learn, PyTorch, TensorFlow, or DeepChem.
• Experience with modern development practices (e.g., Git, CI/CD, AI coding tools) and cloud platforms (Azure/AWS) 
• Proven track-record of achievement and for interdisciplinary project work (membership/leadership) 
• Excellent networking and communication skills
• Team player with good communication and presentation skills to deliver scientific and technical data in a consistent and clear manner
• High degree of self-organization as well as learning agility
• Fluent in English and basic German skills 

WHAT WE OFFER

Our benefits package is flexible, appreciative, and tailored to your lifestyle, because: What matters to you, matters to us! 

• We ensure your financial stability with a competitive salary between 88.900€ and 108.000€ per year (full-time) plus a variable component. Your compensation is based on your qualifications, skills, and professional experience.  
  
• Whether it’s hybrid work models or part-time arrangements: Whenever it is possible, you will have the flexibility to work how, when and where it is best for you.
  
• Your family is a top priority. We offer loving company daycare centers at multiple locations, support in finding childcare, time off for the care of elderly or dependent family members, summer camps for children, and much more.
  
• We support your professional growth by providing access to learning and development opportunities, training programs through the Bayer Learning Academy, development dialogues, as well as coaching and mentoring programs.
  
• We promote health awareness and opportunities for selfcare through various measures, such as free health checks with the company doctor.
  
• We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.

Be You. Be Bayer.

#LI-AMSMEA

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:           ​​ ​   Germany : North Rhine Westfalia : Wuppertal-Aprath​

​​Division: ​               Pharmaceuticals​

Reference Code:  865241​