美国梅奥诊所招聘博士后—数字病理学与人工智能/机器学习

美国梅奥诊所招聘博士后—数字病理学与人工智能/机器学习

Postdoctoral Fellow in Digital Pathology & AI/Machine Learning

Employer

Mayo Clinic

Location

Rochester, Minnesota (US)

Salary

Commensurate with experience

Closing date

27 Oct 2026

Discipline

Computing, Engineering

Job Type

Postdoctoral

Employment - Hours

Full time

Duration

Permanent

Qualification

PhD

Sector

Hospital

Job Details

Location: Rochester, Minnesota

Position Type: Full-time, on-site, fixed-term (2-3 years)

Start Date: November 2026

Overview

We are seeking a highly motivated and innovative postdoctoral research fellow to join the multidisciplinary research team of Dr. Akhilesh Pandey at Mayo Clinic, Rochester, working at the intersection of digital pathology, artificial intelligence (AI), and machine learning (ML).

This position offers an exciting opportunity to develop and apply cutting-edge computational approaches to large-scale biomedical datasets, with a focus on advancing precision medicine in cancer. The successful candidate will work closely with computational scientists, pathologists, and clinicians to build robust AI-driven solutions for biomarker discovery, disease characterization, and translational research.

Key Responsibilities:

Develop, implement, and optimize machine learning/deep learning models for digital pathology image analysis

Analyze large-scale histopathology, omics, and clinical datasets

Design pipelines for image preprocessing, segmentation, feature extraction, and predictive modeling

Collaborate with cross-functional teams to integrate imaging data with genomic/transcriptomic/proteomic data

Contribute to study design, data interpretation, and dissemination of findings in high-impact peer-reviewed journals and present at conferences

Required Qualifications:

Ph.D. in Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, or a related quantitative discipline

Strong background in machine learning/deep learning (e.g., CNNs, transformers, vision models)

Experience working with foundation models (e.g., vision-language models, large multimodal models, or pre-trained foundation models for biomedical imaging)

Proficiency in Python and relevant libraries (e.g., PyTorch, TensorFlow, scikit-learn)

Experience with image analysis pipelines and handling large-scale datasets

Proven ability to conduct independent research and publish results

Strong problem-solving skills and excellent communication abilities

Preferred Qualifications:

Experience in digital pathology or computational pathology

Hands-on experience in fine-tuning, adapting, or deploying foundation models for biomedical or imaging applications

Familiarity with multimodal data integration (e.g., imaging + spatial proteomics, genomics, transcriptomics)

Knowledge of self-supervised learning, contrastive learning, or representation learning approaches

Experience with high-performance computing, cloud platforms, or distributed training

Prior experience working in a collaborative biomedical research environment

What We Offer

Access to state-of-the-art computational resources and high-quality datasets

Opportunities to collaborate with leading experts in pathology, multi-omics technologies, and AI

A highly interdisciplinary and supportive research environment

Competitive salary and benefits package

Strong support for career development, networking, and academic advancement

Application Instructions:

Interested candidates should submit:

Cover letter outlining research interests and experience

Curriculum Vitae (CV)

Contact information for 2–3 references

Applications will be reviewed on a rolling basis until the position is filled.

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