Postdoctoral Researchers, Baslan Lab

University of Pennsylvania; Philadelphia (Philadelphia County); On-site; USD 58,000 - 70,000; Full time

Benefits offered by this job

Mentorship

Freedom

Resources

Exciting Science

Fun

Job summary

The Baslan Lab at the University of Pennsylvania invites applications for Postdoctoral Fellows (computational & experimental) to join a multidisciplinary team studying cancer genomes and Copy Number Alterations. Five positions are available, with models spanning organoids and cell lines, using perturbations such as CRISPR, shRNA, and PROTACs.

Mentorship, access to resources and exciting science are emphasized as part of a collaborative environment within Biomedical Sciences at Penn.

Qualifications

• Proven publication record, including bioRxiv/arXiv acceptable.
• Experimentalists: molecular biology, cell culture, and animal work.
• Computational: NGS data analysis, statistics, ML.

Responsibilities

• Join multidisciplinary team studying cancer genomes and CNAs.
• Develop computational and experimental approaches to analyze data.
• Work with organoid and cell line models.
• Apply perturbation methods like CRISPR/shRNA/PROTACs.

Skills

Publication record

Molecular biology

Cell culture

Animal work

Sequencing data analysis

Statistics

Machine learning

Education

Ph.D.

Tools

CRISPR

shRNA

PROTACs

Single-cell sequencing

In vivo models

Job description

Postdoctoral Researchers, Baslan Lab

Location: University of Pennsylvania - Penn Vet

Open Date: Sep 28, 2026

Description

Faculty Mentor: Timour Baslan, Ph.D. Department: Biomedical Sciences Positions are funded by various grants: federal as well as foundation. Five positions The positions are open to US citizens and foreign nationals. The Baslan Lab at the Department of Biomedical Sciences, the University of Pennsylvania (Penn) is recruiting Postdoctoral Fellows (computational & experimental), 5 positions in total, to join our multidisciplinary team of investigators. Our work focuses on studying cancer genomes, with a specific attention to the genetics and biology of a cryptic class of cancer associated mutations termed Copy Number Alterations (CNAs). These somatic events change the number and composition of chromosomes in cancer cells to yield cancer and immune biology that is almost entirely unknown. To dissect these events, we employ a systems biology, top-down approach where advanced analytics of large datasets are coupled to focused perturbations (ex: shRNA, CRISPR, cDNA screens) in experimental model systems (e.g. organoid & cell line models). We also apply a bottom-up approach where we employ cutting edge methods to dissect novel model systems we develop (ex: mouse models).

Some of the techniques our group develops and applies are:

• advanced sequencing technologies, at single cell and bulk levels, to generate large multi-modal datasets.
• novel algorithms & computational approaches, based on maths, statistics, & machine learning, to nominate novel cancer therapeutic targets.
• innovative, molecularly engineered model systems in in-vitro and in-vivo settings (e.g. mouse models)
• highly parallel perturbation approaches; CRISPR, shRNA, PROTACs, small molecules

We aim to advance:

• novel therapeutics; targeted as well as immunotherapies
• early diagnostic as well as prognostic tools
• novel technologies that can be leveraged to address outstanding biological questions

Disease areas of focus include, but are not limited to, acute leukemias, sarcomas, as well as breast and pancreatic cancers.

The training/mentorship opportunities are in the following areas (among others):

• Developing computational and chemical biology approaches to advance copy number informed precision therapies.
• Studying cancer-immune cell interactions during cancer initiation and progression using functional biology approaches & advanced in-situ sequencing/data analytics.
• Developing machine learning approaches to advance novel prognostic and diagnostic methods in cancer.
• Dissecting cancer genome evolution using the first of their kind, somatic lineage tracing mouse models, along with human data analysis.
• Developing single-cell as well as circulating tumor free DNA sequencing technologies.
• Designing and applying novel comparative oncogenomic algorithms to advance unifying principles of chromosomal biology in cancer.

Prospective trainees can expect the followings: Mentorship, Freedom, Resources, Exciting Science, & Fun. Further details can be found here: http://baslanlab.com

Candidates should have a Ph.D.

Qualifications:

(1) A proven record of publication (this can include bioRxiv and/or arXiv papers, or about to publish), (2) For experimentalists, skills in one, or all of the following areas are required: molecular biology, cell culture, and animal work, for computational positions, skills in one or all of the following areas are required: next generation sequencing data analysis, statistics, and machine learning. Start date and term are negotiable.

Equal Employment Opportunity Statement:

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.