Auf einen Blick
- Aufgaben: Develop innovative machine learning solutions for biomedical datasets to optimize molecules and improve understanding of diseases.
- Arbeitgeber: Join Bayer, a visionary company dedicated to solving global challenges in health and agriculture.
- Mitarbeitervorteile: Enjoy flexible work options, competitive pay, and comprehensive family support programs.
- Warum dieser Job: Make a real impact in drug discovery while collaborating with diverse, brilliant minds in a supportive environment.
- Gewünschte Qualifikationen: PhD or equivalent in a scientific field, expertise in machine learning, and strong communication skills required.
- Andere Informationen: Position limited to two years; target start date is negotiable.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
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.
Machine Learning Scientist Bio Modelling (all Genders)
Develop innovative machine learning solutions to analyze biomedical datasets of different modalities with the goal of designing optimized molecules and improving our understanding of targets, diseases and patients.
YOUR TASKS AND RESPONSIBILITIES
- Be an active member of a highly interdisciplinary and cross-organizational team
- Develop and evaluate state-of-the-art machine learning algorithms applied to modelling protein-ligand and protein-protein complexes
- Collaborate with cross-functional teams throughout R&D to ensure innovative algorithmic solutions are operationalized and integrated into our discovery pipelines
- Keep up to date with the latest advances in machine learning technologies
- Engage with the broader scientific community through publications, open-source projects, and conference presentations
WHO YOU ARE
We are excited about your talent and passion for this position. Attracting the right talent is important to us. We would be happy to work with you to identify and create the career and development opportunities you are looking for – also in part-time. And if you don\’t meet all the requirements, we still look forward to receiving your application. We are all constantly learning!
Required:
- You have a highly scientific or engineering background, with a PhD degree or equivalent
- You have expertise in machine learning research
- You have a sincere interest in drug discovery and the life sciences
- You have excellent written and verbal communication skills in English
Preferred:
- You have expertise in bioinformatics or structural biology
- You are an expert in applying machine learning for characterizing and designing small molecules, DNA/RNA, or proteins
- You have expertise in applying, dissecting, and improving upon state-of-the-art machine learning methods. Knowledge of modern generative modelling methods (e.g., diffusion), protein language models (e.g., ESM), modern structure prediction methods (e.g., AlphaFold), or experience efficiently training and fine-tuning large models are a big plus
- You have excellent software engineering skills
- You have a strong publication record or demonstrated contributions (e.g., open source) for the above
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 through a competitive compensation package, consisting of an attractive base pay and our annual bonus. In addition, managers can recognize special contributions by granting an individual performance award or top performance award.
- 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 self-care through various measures, such as free health checks with the company doctor and our health platform #machfit.
- We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.
The position is limited to two years.
Our target date to fill the position is 01.01.2025 (negotiable).
Be You. Be Bayer.
Location: Germany : Berlin : Berlin || Germany : North Rhine Westfalia : Monheim
Division: Pharmaceuticals
Reference Code: 822732
#J-18808-Ljbffr
Machine Learning Scientist Bio Modelling (all Genders) Arbeitgeber: Bayer AG

Kontaktperson:
Bayer AG HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Scientist Bio Modelling (all Genders)
✨Tip Number 1
Engage with the scientific community by attending conferences and workshops related to machine learning and bioinformatics. This will not only expand your network but also keep you updated on the latest advancements in the field, which is crucial for a role at Bayer.
✨Tip Number 2
Showcase your expertise in machine learning and bioinformatics through open-source projects or publications. Having a strong portfolio can significantly enhance your visibility and demonstrate your commitment to the field.
✨Tip Number 3
Familiarize yourself with Bayer's current research initiatives and projects in drug discovery. Understanding their goals and challenges will help you tailor your discussions during interviews and show your genuine interest in contributing to their mission.
✨Tip Number 4
Prepare to discuss your experience with state-of-the-art machine learning methods and how they can be applied to biomedical datasets. Being able to articulate your knowledge and practical applications will set you apart as a candidate.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Scientist Bio Modelling (all Genders)
Tipps für deine Bewerbung 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Scientist position at Bayer. Tailor your application to highlight your relevant experience in machine learning and drug discovery.
Highlight Your Expertise: In your CV and cover letter, emphasize your scientific or engineering background, particularly your PhD and any specific expertise in machine learning, bioinformatics, or structural biology. Mention any relevant projects or publications that showcase your skills.
Showcase Communication Skills: Since excellent written and verbal communication skills are required, ensure your application materials are well-written and clearly articulate your ideas. Consider including examples of how you've effectively communicated complex concepts in previous roles.
Express Your Passion: Bayer values candidates who are passionate about making a difference in health and life sciences. In your application, convey your enthusiasm for the role and the impact you hope to have in drug discovery and biomedical research.
Wie du dich auf ein Vorstellungsgespräch bei Bayer AG vorbereitest
✨Show Your Passion for Drug Discovery
Make sure to express your genuine interest in drug discovery and life sciences during the interview. Share any relevant experiences or projects that highlight your enthusiasm and commitment to this field.
✨Demonstrate Your Technical Expertise
Be prepared to discuss your experience with machine learning algorithms, especially those related to bioinformatics or structural biology. Highlight specific projects where you applied these techniques and the impact they had on your research.
✨Engage with Interdisciplinary Collaboration
Since the role involves working in a cross-organizational team, emphasize your ability to collaborate effectively with diverse teams. Share examples of how you've successfully worked with others to achieve common goals in previous roles.
✨Stay Updated on Latest Technologies
Show that you are proactive about keeping up with advancements in machine learning and biomedical research. Mention any recent publications, conferences, or open-source projects you’ve engaged with to demonstrate your commitment to continuous learning.