Several postdoctoral positions, for both computational and experimental researchers, are open in the BioCiphers lab at the University of Pennsylvania. The lab, led by Prof. Yoseph Barash, is part of the Institute for Biomedical Informatics, and is joint between the Department of Genetics at the School of Medicine and the Department of Computer and Information Science at the School of Engineering.
The BioCiphers lab develops machine/deep learning algorithms and statistical models that integrate high-throughput data Genomics (RNASeq, CLIPSeq, etc.) and Genetics data to infer RNA biogenesis and function as these related to human disease.
Together with several labs across the Perelman School of Medicine (PSOM) and the Children’s Hospital of Philadelphia (CHOP) the BioCiphers Lab is also developing innovative functional genomics approaches that integrate short/long read sequencing, CRISPR/Cas9 genome-editing and high-throughput screening to study the regulation and functional impact of RNA processing.
Three types of research positions are available, as described below. These positions may also be joint with other mentors/labs across PSOM/CHOP depending on the specific project.
We are looking for candidates with a strong background in machine learning and track record in developing deep learning models. Background and experience with genomic and genetic data is preferred but not mandatory. The ideal candidate will have a track record of scientific productivity and leadership publishing applied statistical models and/or ML/DL papers in leading journals/conferences (e.g. ISMB/RECOMB, ICML/NeurIPS/ICLR). The ideal candidate will demonstrate a working proficiency in programming, scripting and statistical computing (i.e., C/C++, Python, PERL, R, etc.), DL libraries (eg. TF, Pytorch, Edward), will have experience handling large data sets in the UNIX/LINUX operating environment, and experience with cloud computing.
We are looking for candidates with a strong background in Bioinformatics and experience analyzing large volumes of genomic and genetic data. Experience/background in RNA Genomics data (RNASeq, long reads, CLIP-Seq, Ribo-Seq, SHAPE, etc.) is preferred. The ideal candidate will have a track record of scientific productivity and leadership publishing genomic analysis and methods in leading journals. Candidates are expected to have proficiency in programming, scripting and statistical computing (i.e., C/C++, Python, PERL, R, etc.) handling large data sets in the UNIX/LINUX operating environment. Experience with cloud and distributed computing is a plus.
Experimental & Genomics postdoc:
We are looking for candidates to lead the development and consequent analysis of novel technology involving CRISPR/single-cell RNA/bulk RNA sequencing (depending on the exact project). The newly developed assays are aimed to measure and subsequently predict/model different aspects of RNA processing and the effect of genetic variations as they relate to human disease. The technology development will be followed with integrative analysis that combines multiple sources of genomic and genetic data to make new discoveries at the forefront of RNA processing regulation and specific disease contexts.
Candidates are expected to have proficiency in molecular biology techniques and/or next-generation sequencing based assays. Experience in RNA biology, single-cell sequencing assays or high-throughput approaches (ie. genetics screens, massively parallel reporter assays) is preferred. Prior experience with genomics and data analysis, or a strong interest/capacity for learning genomics/bioinformatics and analysis of next-generation sequencing data (ie. through interactions with other BioCiphers lab members), is a plus.
To apply, please send (i) a cover letter that includes the names and contacts for three
references and a short statement of research interests, and (ii) a current CV to:
Yoseph Barash, PhD (firstname.lastname@example.org). Further information about the lab can be
found at: http://biociphers.org
The University of Pennsylvania is located at the heart of Philadelphia. The University of Pennsylvania is an equal opportunity and affirmative action employer.