Postdoctoral Fellow, Computational Biology in Cancer – Chan Lab

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe.

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Exciting Opportunity at MSK: Postdoctoral Fellow, Computational Biology in Cancer – Chan Lab

The Chan Lab in the Human Oncogenesis & Pathogenesis Program at MSK is seeking an exceptionally motivated Postdoctoral Fellow in Computational Biology. This is an ambitious opportunity to join a new multidisciplinary team committed to developing innovative machine learning methods to study cancer metastasis and resistance mechanisms. Engage in world-class research using single-cell and cell-free sequencing as well as spatial imaging.

Explore more about the lab at www.joechanlab.org.

Role Overview:

The Postdoctoral Fellow will focus on both methodological development and the analysis of large-scale patient datasets. This role involves developing software packages, contributing to manuscript writing, and participating in collaborative research. The position requires engaging with a vibrant scientific community through regular lab meetings and academic activities. The aim is to quantify flexibility in lineage, gain insights into molecular machinery, and identify new drug targets.

Representative Publications Include:

1. Chan, et al. Lineage plasticity in prostate cancer depends on JAK/STAT inflammatory signaling. Science, 2022. 
2. Chan, et al. Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer. Cancer Cell, 2021. 
3. Schoenfeld,  Chan, et al. Tumor analyses reveal squamous transformation and off-target alterations as early resistance mechanisms to first-line osimertinib in EGFR-mutant lung cancer. Clinical Cancer Research, 2020.  
4. Offin,  Chan, et al. Concurrent RB1 and TP53 alterations define a subset of EGFR-mutant lung cancers at risk for histologic transformation and inferior clinical outcomes. Journal of Thoracic Oncology, 2019.  
5. Chan, et al. Topology of viral evolution. PNAS, 2013.  
6. Singh,  Chan, et al. Transforming Fusions of FGFR and TACC Genes in Human Glioblastoma. Science, 2012.  

7. Finlay JB, ..., Chan JM, Goldstein BJ, Oliver TG. Olfactory neuroblastoma mimics molecular heterogeneity and lineage trajectories of small-cell lung cancer. Cancer Cell. 2024 Jun 10.

Key Qualifications:

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related field, or equivalent experience
• Proven proficiency in Python and R
• Prior experience in computational biology
• Demonstrated ability to engage in independent thinking
• Excellent written and verbal communication skills
• Collegiality as a team member and willingness to mentor other trainees
• At least one published first-author manuscript

Core Skills:

• Expertise in data analysis and statistical modeling
• Ability to compete successfully in a fast-paced and dynamic research environment
• Strong problem-solving skills and attention to detail
• Outstanding ability to collaborate and communicate with cross-functional teams

Additional Information:

This position provides an outstanding opportunity to advance your career while making significant contributions to cancer research. Collaborate with a dedicated team to successfully implement innovative solutions in an encouraging and inclusive environment.

Pay Range: $70,000 to $85,000 (depending on postgraduate experience).

Contact:

If you have any questions about this job opportunity, please contact:  

Dr. Joseph M. Chan, MD, PhD

chanj3@mskcc.org

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