Senior Deep Learning Engineer - Computer Vision
OmicVision BiosciencesAbout OmicVision Biosciences
OmicVision Biosciences is an ambitious early-stage biotech start-up based in Copenhagen's renowned BioInnovation Institute (BII). Our goal is to leverage the power of spatial proteomics and revolutionize precision medicine. Our forward-thinking platform allows us to delve into the complexities of protein expression at a single-cell level, unveiling unique insights into health and disease. Our commitment is to enable precision therapies powered by data, with a vision to drive significant enhancements in patient outcomes.
The Role
As a Senior Deep Learning Engineer, your mission will be to lead the charge in computational pathology, applying your deep learning expertise to construct and refine powerful AI models that are supercharged with proteomics data. Your models will be the driving force analyzing immense histological data sets, extracting biological insights with unmatched precision and insight.
Responsibilities
- Develop and optimize deep learning models for histology slide segmentation and region-of-interest identification.
- Implement and maintain the infrastructure for tracking and evaluating models.
- Collaborate with cross-functional teams to integrate deep learning models into our production environment.
- Continuously research and implement the latest advancements in computer vision and deep learning applicable to histopathology.
- Work closely with biologists and experts to understand domain-specific challenges and incorporate biological insights into model development.
Qualifications
- Advanced Degree in Computer Science, Engineering, or a Related Field: Master's or Ph.D. with a minimum of 2-5 years of industry experience in a relevant domain.
- Industry experience is highly valued.
- Ability to train, evaluate, and fine-tune the latest generation of vision models using both large-scale public datasets and proprietary datasets.
- Deep understanding of feature embeddings and their practical applications in visualization, clustering, and classification.
- Expertise in Python programming tailored towards data science and machine learning projects.
- Proficient in PyTorch and familiar with Unix-based operating systems, including experience with Linux.
- Familiarity with model tracking and versioning tools (e.g., Neptune.ai, Weights & Biases).
Nice to Have
- Experience with Cutting-Edge Self-Supervised Learning Frameworks: Hands-on experience with technologies such as Masked Autoencoders, iBOT, DinoV2, or similar.
- Competency in managing high-performance computational resources for processing large-scale datasets, such Gigapixel or Whole Slide Images (WSIs).
- Domain-Specific Knowledge of biology, especially computational pathology or proteomics.
- Publications or a strong portfolio in relevant fields.
Benefits Extracted with AI
- Health insurance
- Paid vacation
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