Computational Histopathology Analyst

Computational Histopathology Analyst

Upper Providence, Pennsylvania- onsite

Contract

The engagement is structured around three pillars of expertise that CLIENT considers non-negotiable for candidate success:

Position Summary

The Computational Histopathology Analyst will leverage deep expertise in image analysis, machine learning, and histotechnology to develop, validate, and execute computational pathology algorithms that drive biomarker discovery and translational research at CLIENT. The individual will own end-to-end algorithm development using Halo AI (preferred commercial platform), support metadata ingestion workflows into CLIENT's Image Management System, and contribute hands-on wet lab capabilities to support tissue processing inputs for computational analysis. All work is conducted under CLIENT Google Cloud Platform-aligned validation SOPs with documentation maintained in Electronic Lab Notebooks (ELN) and Veeva Vault.

Key Responsibilities

A. Computational Pathology - Algorithm Development & Validation (Primary)

• Develop, optimize, and validate image analysis algorithms and computational pathology pipelines using commercial software - preferred platform: Halo AI; accepted alternatives include Visiopharm, CellProfiler, Imaris, and QuPath.
• Execute end-to-end algorithm development lifecycle: method development, internal testing, formal validation, and data delivery per CLIENT milestone schedule.
• Deliver five complete computational pathology algorithms over the 12-month engagement, each with accompanying validation report and QC-reviewed data output.
• Apply machine learning and quantitative image analysis techniques to analyze histological tissue samples and generate robust biomarker insights.
• Utilize whole-slide imaging platforms and advanced microscopy tools for qualitative and quantitative data interpretation.
• Ensure all algorithmic outputs meet CLIENT acceptance criteria before submission for sign-off; perform QC review on all executed data prior to delivery.
• Document all development and validation activities in CLIENT's Electronic Lab Notebook (ELN) and regulatory documentation systems including Veeva Vault, in compliance with Google Cloud Platform standards.

B. Metadata Ingestion & Data Integration

• Design and implement two semi-automated metadata ingestion workflows into CLIENT's Image Management System to support downstream pathologist and computational analysis pipelines.
• Perform structured metadata mapping across four projects, linking sample metadata to corresponding images in the Image Management System and flagging discrepancies for escalation.
• Manage and organize pathology image metadata to ensure accuracy, consistency, and downstream pipeline readiness.
• Perform data wrangling across multiple file types and formats; apply coding or scripting skills (Python, R, or equivalent) to automate reconciliation tasks where appropriate.
• Maintain rigorous data integrity standards; attention to detail and systematic error-flagging are critical success factors for this role.

C. Wet Lab / Histotechnology Support (Nice-to-Have, Milestones Included)

• Support wet lab histotechnology workflows to produce tissue inputs for computational analysis, including:
  • Microtomy - sectioning of tissue samples to appropriate thickness for staining and imaging
  • Histological staining - applying and QC-reviewing staining protocols for IHC and special stains
  • Slide scanning and whole-slide imaging using automated platforms
  • Image QC and quality assessment prior to ingestion into computational pipelines
• Operate and oversee automated staining platforms including Ventana Benchmark / Discovery Ultra, Leica Bond RX / Bond III, and Dako Link 48/96; industry-based automated platform experience is strongly preferred over academic manual staining backgrounds.
• Execute five wet lab sample testing assays (Months 7 11), each including full microtomy, staining, imaging, and QC cycle.
• Coordinate tissue processing schedules with computational analysis timelines to ensure smooth handoff of slide inputs into digital pathology workflows.

D. Governance, Documentation & Collaboration

• Maintain all project documentation in CLIENT's ELN and Veeva Vault in accordance with Google Cloud Platform-aligned validation SOPs and regulatory requirements.
• Actively participate in governance meetings and control gates; report progress against milestones and flag risks proactively.
• Collaborate with CLIENT MSAT, QA, Operations, and QC teams in weekly technical intake sessions to gather process information required for algorithm authoring.
• Operate as an independent contributor - self-directed, organized, and capable of managing multiple concurrent deliverables against fixed milestone dates.
• Escalate data errors, ambiguities, and timeline risks promptly to the CLIENT SUS Project Manager with proposed resolution plans.

Required Qualifications & Experience

Education

• PhD in a relevant field (Pathology, Computational Biology, Bioinformatics, Biomedical Engineering, Cell Biology, or closely related discipline) with postdoctoral research experience - strongly preferred.
• Master's degree with substantial industry experience in a pharmaceutical, biotech, or CRO environment is acceptable where depth of practical expertise compensates.
• Entry-level PhD candidates without postdoctoral or equivalent industry experience are not suitable for this engagement.

Experience Level

• Senior or Principal Scientist level (equivalent to CLIENT Grade G7 or above).
• Minimum 3+ years post-PhD applied experience in computational pathology, digital pathology, or closely related field.
• Demonstrated ability to function as an independent contributor with minimal day-to-day supervision.

Technical Skills & Competencies

Computational Pathology - Must Have

• Proficiency in commercial image analysis software - Halo AI is the top-priority platform; candidates must demonstrate hands-on experience or demonstrate rapid adaptability.
• Accepted alternative platforms with strong experience: Visiopharm, CellProfiler, Imaris (Amira/Amaris), QuPath, ImageJ/Fiji.
• Expertise in designing, developing, and validating image analysis algorithms for histological tissue data including cell detection, segmentation, and biomarker quantification.
• Applied knowledge of machine learning and computer vision methods relevant to histopathological image analysis.
• Experience working with whole-slide images (WSI) and digital pathology file formats.

Wet Lab / Histotechnology - Preferred

• Hands-on experience in core histology workflows: tissue processing, microtomy, embedding, staining, and slide preparation.
• Proficiency with automated immunohistochemistry (IHC) and special staining platforms:
  • Ventana Benchmark / Discovery Ultra
  • Leica Bond RX / Bond III
  • Dako Link 48/96
• Slide scanning and whole-slide imaging experience; familiarity with scanning platforms and image QC protocols.
• Industry-based automated staining experience strongly preferred over academic manual techniques.

Data Integration & Informatics - Must Have

• Ability to design and build semi-automated metadata ingestion workflows; experience integrating metadata into image management or laboratory information management systems (LIMS).
• Proficiency in data wrangling and reconciliation across multiple file types and formats; rigorous attention to detail and error-flagging capability.
• Basic to intermediate coding/scripting skills - Python, R, or equivalent - for automation, data transformation, and pipeline support.
• Experience working with ELN systems and regulatory documentation platforms such as Veeva Vault is a significant advantage.

Google Cloud Platform & Regulatory Documentation

• Understanding of Google Cloud Platform-aligned validation frameworks and SOPs applicable to computational method development and data delivery in a pharmaceutical R&D context.
• Experience preparing and maintaining validation reports, method development documentation, and regulatory submission-ready records.

Ideal Candidate Profile

CLIENT is not evaluating teams or groups - this engagement requires a single, highly capable individual who brings all three pillars of expertise with depth in computational pathology as the primary domain. The ideal candidate:

• Has built and validated image analysis algorithms in a regulated pharmaceutical or biotech environment - not just academic research settings.
• Understands the full data lifecycle in digital pathology: from slide preparation through image acquisition, computational analysis, metadata management, and regulatory documentation.
• Is self-organizing, detail-oriented, and capable of simultaneously managing five concurrent algorithm workstreams against fixed milestone dates.
• Has a troubleshooting mindset - able to identify data errors, algorithm performance issues, and process gaps and escalate with a clear proposed resolution.
• Is comfortable working onsite in a team environment, attending regular technical intake sessions, and communicating progress and blockers transparently.
• Brings a track record of generating high-quality, reproducible analytical data that passes formal validation review.

Tools & Systems Environment

CLIENT will provide all software licenses, hardware, and system access. The contractor is not required to supply tools. Key platforms include:

Ayush Sharma Sr. US Technical Recruiter

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