Nationality: International Students
Application deadlines: Open
The laboratory of Dr Zizhang Sheng at Columbia University uses bioinformatics and biochemical approaches to elucidate the mechanisms of the humoral immune response to infection (HIV, SARS-CoV-2, influenza, malaria, etc.) and to understand the role and origin of autoreactive B cells in autoimmunity (systemic lupus erythematosus, IgA nephropathy, etc.).
Further descriptions of the Sheng laboratory can be found here:
The Sheng lab pursues scientific research in cutting-edge fields and has published more than 80 papers in Cell, Nature, Nature Communications, Cell Reports, etc.
We are seeking a highly motivated and talented individual to join our team as a Bioinformatics Postdoctoral Research Fellow.
This position offers an exciting opportunity to contribute to cutting-edge research in the field. The position will involve analysing next generation sequencing data of single cell transcriptomes and antibody repertoires to study affinity maturation mechanisms of pathogen or autoantigen specific antibodies and disease pathogenesis. The position may also involve the development of machine learning and/or deep learning methods to predict the potency of HIV broadly neutralising antibodies.
In addition to NGS analysis skills, experience in structural bioinformatics, deep learning or biochemical assays including protein expression and production, ELISA, SPR are preferred.
The successful candidate will work closely with a multidisciplinary team of computational and experimental researchers and will gain valuable experience in advanced data analysis techniques, algorithm development and interpretation of NGS data.
- PhD in bioinformatics, computational biology, genomics or a related field.
- Strong programming skills in languages such as Python, R or Perl.
- Proficiency in the use of bioinformatics software and tools (e.g. CellRanger, Seurat, SAMtools, etc.).
- Experience in next-generation sequencing data analysis (e.g. RNA-Seq, antibody repertoire).
- Knowledge of statistical analysis and machine learning techniques.
- Excellent problem solving skills and ability to work both independently and collaboratively.
- Effective communication skills, including the ability to present research findings to a variety of audiences.
- A strong publication record and a demonstrated passion for bioinformatics research.
Interested candidates are invited to submit the following documents to the Columbia ASR system (https://apply.interfolio.com/135947) or email to [email protected].