We are seeking to add a digital pathology lab assistant/specialist to our India operations. In this role, you will supervise and support the digitization efforts of large-scale cancer histology workloads. You will be working on a variety of projects across several leading health organizations and prepare high-quality scans of microscope slides containing tissue sections for pathology review.
Key responsibilities:
1. Organize and QC stained tissue slides
2. Work on the barcode and file stained slides and paperwork
3. Review the schedule of priorities and adjust workflow accordingly
4. Enter specimen testing results into Excel spreadsheets
5. Update project trackers
6. Clean slides and load them into whole slide scanners
7. Perform a QC check of scanned slides to ensure the tissue is in focus
8. Upload scans to the database
9. File slides and paperwork
10. Troubleshoot scanners and software
1. Those who are from or open to relocate to Raipur, Naya Raipur and neighboring cities
High attention to detail
Strong Excel skills
Organized and a drive to learn and grow with the department and company
Minimum qualifications - high school diploma or equivalent
Basic computer skills
6-months previous clinical laboratory/lab technician/histology experience
Successful completion of a laboratory assistant program
Basic knowledge of histology & tissue specimen requirements and handling
Knowledge of medical terminology
Additional related education and/or experience
Experience with Microsoft Excel and other Office programs
Annual CTC: ₹ 3,00,000 - 3,10,000 /year
Annual CTC breakup:
1. Fixed component: 80%
2. Variable component: 20%
Crosscope is a medical AI software company developing cutting-edge deep learning technology for pathologists to speed up diagnosis and deliver data-driven insights through imaging biomarkers in rendering a more accurate and reliable cancer diagnosis.
Crosscope is a medical AI software company developing cutting-edge deep learning technology for pathologists to speed up diagnosis and deliver data-driven insights through imaging biomarkers in rendering a more accurate and reliable cancer diagnosis.
