Computational Pathology Scientist
Aptask Global Workforce (AGW) is seeking a Computational Pathology Scientist - Onsite for a 6-month contract position with a Global Biotechnology Company located in South San Francisco, CA.
This role is part of a Digital Pathology team focused on revolutionizing the analysis of digital histopathology slides by leveraging computational methods. The ideal candidate will contribute to the development and application of image-processing methods and pipelines using both conventional and advanced techniques, such as machine learning and deep learning.This position requires close collaboration with pathologists to design and execute image analysis workflows, as well as working with computational and data scientists across various departments.
Responsibilities:
- Contribute to the development and application of image-processing methods and pipelines
- Utilize both conventional techniques and advanced techniques, such as machine learning and deep learning
- Perform basic statistical analyses and data visualizations
- Collaborate with pathologists to design and execute image analysis workflows tailored to biological questions
- Work with computational and data scientists across various departments
Requirements:
- MS or PhD-level scientist with a minimum of 5 years of experience
- Strong programming foundation with demonstrated proficiency in Python and its scientific computing ecosystem (NumPy, Pandas, Scikit-learn, OpenCV)
- Proficiency with version control systems, particularly Git, and experience with collaborative platforms like GitHub or GitLab
- Solid experience in both classical and modern image analysis techniques, including traditional image processing and applying machine learning for tasks like image classification and semantic segmentation
- Hands-on experience processing and analyzing gigapixel whole-slide images (WSI), using libraries such as OpenSlide or similar tools
- Strong aptitude for iterative design and a proactive approach to receiving and incorporating feedback from cross-disciplinary teams
- Excellent interpersonal and communication skills, with a proven ability to explain complex computational concepts to pathologists and biologists
Desired skills:
- Deep expertise in developing and implementing advanced deep learning models for digital pathology, including for tasks like instance segmentation
- High proficiency with at least one major framework such as PyTorch, TensorFlow, or Keras
- Experience using High-Performance Computing (HPC) environments and familiarity with job schedulers, specifically SLURM
- Practical experience with commercial digital pathology platforms (e.g., HALO, Visiopharm, or QuPath)
- Experience building and managing data pipelines with workflow orchestration tools such as Dagster or Airflow
- Experience building simple graphical user interfaces (GUIs) for research tools using Python frameworks like Tkinter or PyQt
- Familiarity with cloud computing services for model training and deployment, particularly Amazon Web Services (AWS EC2)
Pay range: up to $67.20 per hour
Only candidates available and ready to work directly as Aptask Global Workforce (AGW) employees will be considered for this position.
If you have the described qualifications and are interested in this exciting opportunity, apply today!
Aptask Global Workforce (AGW)
ApTask Global Workforce (AGW) is a certified Minority and Veteran workforce solutions company. AGW delivers operational, clinical, lab and professional talent with a strong focus on healthcare and life sciences. The company supports clients with reliable staffing, program expertise and a commitment to quality, speed and consistent delivery.
Benefits of working with ApTask Global Workforce include:
- Medical
- Dental
- Vision
- Sick Pay (for applicable states/municipalities)
Our team stays close to the process and is here to guide you every step of the way. To learn more, please visit our website
ApTask Global Workforce is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability or status as a protected veteran.