Postdoctoral Researchers, Baslan Lab

University of Pennsylvania; Erie (Erie County); On-site; USD 55,000 - 75,000; Full time

Job summary

The Baslan Lab at the University of Pennsylvania's Department of Biomedical Sciences invites applications for Postdoctoral Fellows (computational & experimental), five positions in total, to study cancer genomes and Copy Number Alterations using systems biology and cutting-edge perturbation models. We seek candidates with a Ph.D.

and strong skills in molecular biology, sequencing analytics, statistics, and machine learning (experimentalists or computationally focused).

Qualifications

• Ph.D. required for Postdoctoral Fellows in cancer genomics.
• Experimentalists: molecular biology, cell culture, and animal work.
• Computational positions: next generation sequencing data analysis, statistics, and ML.

Responsibilities

• Conduct computational and experimental studies on cancer genomics.
• Collaborate with multidisciplinary team and mentor junior researchers.
• Publish findings in peer-reviewed journals and present at conferences.

Skills

Molecular biology

Cell culture

Animal work

NGS data analysis

Statistics

Machine learning

Computational biology

Education

Ph.D.

Tools

CRISPR

shRNA

PROTACs

Job 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

• A proven record of publication (this can include bioRxiv and/or arXiv papers, or about to publish),
• 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.

Candidates should have a Ph.D.

Applicants are required to submit the following materials through Interfolio:

• CV
• Cover letter
• A list of 3 referees

Questions or follow up inquiries can be emailed to Dr. Baslan at [e-mail]

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.