Postdoc in Computational Cancer Biology & Cell Plasticity

Memorial Sloan Kettering Cancer Center; New York (NY); On-site; USD 72,000 - 87,000; Full time

Job summary

Memorial Sloan Kettering Cancer Center in New York seeks a highly motivated postdoctoral fellow to study tumor cell plasticity using computational approaches. The role combines single-cell and spatial genomics, cfDNA profiling, and machine learning in a translational computational oncology setting.

The candidate will develop methods, interpret results, and contribute to manuscript writing, collaborating across a vibrant scientific community and lab meetings. A strong publication record is valued.

Qualifications

• A PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related field.
• Proficiency in Python and R.
• Prior experience in computational biology.
• Ability to engage in independent thinking.
• Excellent written and verbal communication.
• Collegiality as a team member and willingness to mentor trainees.
• At least 1 published first-author manuscript.

Responsibilities

• Develop and apply computational methods to study lineage plasticity.
• Biological interpretation of results and manuscript assistance.
• Lead or contribute to manuscript writing and presentations.
• Engage in regular lab meetings and scientific discussions.

Skills

Python

R

Independent thinking

Written and verbal communication

Mentoring others

Education

PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or related field

Job description

Memorial Sloan Kettering Cancer Center in New York seeks a highly motivated postdoctoral fellow to study tumor cell plasticity using computational approaches. The role combines single-cell and spatial genomics, cfDNA profiling, and machine learning in a translational computational oncology setting.

The candidate will develop methods, interpret results, and contribute to manuscript writing, collaborating across a vibrant scientific community and lab meetings. A strong publication record is valued.