Job Title: Post-Doctoral Fellow in Image Processing for Spatial Proteomics
Location: Stanford School of Medicine, Stanford, CA
Department: Canary Center for Cancer Early Detection
Position Type: Post-Doctoral Fellowship
About Us:
The Stanford School of Medicine is a leading institution dedicated to advancing biomedical research and improving patient care. Our team is committed to exploring innovative technologies that enhance our understanding of biological processes at single-cell resolution. The Mallick Lab, is focused on the development of approaches to understand diseases like cancer and Alzheimer’s Disease from a multi-scale systems perspective that integrates novel technologies with advanced experimentation and computation to understand disease origins and progression.
Project Overview:
We are collaborating with the Zavaleta lab at USC developing a novel imaging modality aimed at enhancing our ability to visualize and analyze protein expression in single cells within their spatial context in pathomic samples. This research opportunity will be focused primarily on the development and application new image processing and machine learning techniques to enable high-resolution interpretation of single-cell, spatial proteomic data.
The successful candidate will be responsible for leveraging insights from single-cell and spatial data to ask an answer systems biology questions about cellular functions and interactions and cellular heterogeneity in complex tissue environments, such as cancer and Alzheimer’s disease. This role involves working in a dynamic environment and conducting integrative analyses of multidimensional datasets.
Key Responsibilities:
- Develop and optimize image and signal processing techniques to improve data quality and data acquisition for single-cell analysis.
- Analyze and interpret spectral and image data, providing statistical insights that contribute to the optimization of the imaging methodology.
- Contribute to the design and execution of experimental protocols, ensuring the integration of imaging and proteomics methodologies.
- Develop and implement computational and systems biology approaches for microenvironment analysis from spatial omics and single-cell omics data.
- Mentor graduate students and contribute to the overall educational environment of the laboratory.
- Collaborate with interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights.
- Perform integrative analyses of multidimensional datasets within the context of cancer and Alzheimer’s disease.
- Communicate research findings through presentations, publications, and conferences.
- Contribute to the development of grant proposals and funding applications.
Qualifications:
- Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, mathematics, electrical engineering, physics, or a related field with a focus on image and signal processing.
- Strong knowledge in bioinformatics, machine learning, statistics and programming skills (Python, or C++) are required.
- A strong background in quantitative imaging techniques and proficiency in computational analysis of imaging data and image processing algorithms.
- Familiarity with proteomics or spatial biology methodologies is a plus but not required.
- Excellent communication skills, both written and verbal, with the ability to work collaboratively in a team-oriented environment.
- A strong publication record in peer-reviewed journals is desirable.
- Excellent verbal and written communication skills are essential.
Application Process:
Interested candidates should submit a cover letter, CV, and contact information for three references to spatialbio_applicants@mallicklab.org. In your cover letter, please include a brief statement of research interests and how your background aligns with the goals of the project.
Join us at Stanford to advance the frontiers of spatial proteomics and make impactful contributions to the field of biomedical research!
Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.
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