Sr. Machine Learning Engineer / Researcher – Multimodal Spatial Omics
Are you passionate about how technology can make a real impact in cancer? Join us at kaiko in building the state-of-the-art Data & AI platform, enabling large-scale training of multi-modal foundation models, and transforming the clinical workflow to deliver better patient outcomes.
Our culture
At Kaiko, we have an open, creative and non-hierarchical work atmosphere which offers continuous learning and direct impact in return for accountability and team spirit.
We offer flexibility - for instance, through hybrid working – alongside an expectation for managing and delivering your own goals; our team’s ownership, passion and shared commitment to improving health outcomes through data is something that sets us apart.
At the intersection of healthcare and data we recognize the implications on wellbeing and trust and approach our work with the utmost sensitivity. Data privacy, compliance and security are core to everything we do. Our open, creative environment gives talented people room to explore new ideas and we reward this with an attractive package and opportunities for further personal development.
About the Role
At Kaiko, we are working towards multimodal foundation models for oncology. As a Sr. Machine Learning Engineer / Researcher specializing in multimodal spatial omics, you will be conceptualizing and driving projects to build uni- and multi-modal foundation models for transcriptomics, proteomics and/or other omics data, utilizing spatial information to join different modalities including omics, images, text captions etc., exploring ways to use one modality to improve the other, and join them. You will work within our ML Research Team and collaborate closely with clinicians, researchers from hospitals and our academic collaborators.
Responsibilities
- Conceptualize, plan and execute research projects in the field of multimodal spatial omics, and towards multimodal foundation models for oncology.
- Work together with the product team and other ML teams to bring the FM capabilities to the clinic.
- Coordinate ML research projects, guiding team members, managing academic collaborations, setting project goals, and ensuring the successful execution of research initiatives.
You Have
- Educational Background: Ph.D. in computer science, Engineering, biology, oncology, omics or a related field.
- ML Research: A strong background in Machine Learning Research.
- Spatial omics: Experience in working with spatial transcriptomics, proteomics etc. in a machine learning context. Publications in relevant journals and conferences is a plus (NeurIPS, ICLR, CVPR, ECCV, ICML, MICCAI, etc.).
- Programming Expertise: Proficient in Python with extensive experience in PyTorch.
- Large scale training: Experience in training large scale machine learning models.
- Problem-Solving: Ability to diagnose and resolve complex technical challenges related to GPU acceleration and distributed training.
- Collaboration: Excellent communication skills and ability to work effectively within a multidisciplinary team.
- Adaptability: Capable of managing multiple projects simultaneously and adapting to evolving priorities in a fast-paced environment.
Additional Information
This position is full-time and requires residency in either the Netherlands or Switzerland, a valid work permit, and proximity to our offices in Amsterdam or Zürich. A Certificate of Conduct will be necessary upon finalizing the employment contract due to the handling of sensitive data.
What can you expect?
At Kaiko we have an open, creative and non-hierarchical work atmosphere which offers continuous learning and direct impact in return for accountability and team spirit.
We offer flexibility - for instance, through remote working – alongside an expectation for managing and delivering your own goals; our team’s ownership, passion and shared commitment to improving health outcomes through data is something that sets us apart.
At the intersection of healthcare and data we recognize the implications on wellbeing and trust and approach our work with the utmost sensitivity. Data privacy, compliance and security are core to everything we do. Our open, creative environment gives talented people room to explore new ideas and we reward this with an attractive package and opportunities for further personal development.
- Department
- ML Ops
- Locations
- Amsterdam (NKI-AvL), Zürich (Puls 5), Amsterdam (Lab42)
- Remote status
- Hybrid Remote
Sr. Machine Learning Engineer / Researcher – Multimodal Spatial Omics
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