Computational Biology Team
In the Sean N. Parker Center for Allergy and Asthma Research at Stanford University, we collect clinical as well as environmental data and utilize many high-throughput experimental technologies, which all together generate large amounts of data. In order to analyze and use these big data sets properly, our Center has formally established a bioinformatics core in 2015. Our team of computational biologists and bioinformaticians is constantly growing. Our projects include a wide spectrum - from the analysis of original clinical trial data to multi-omics cutting-edge analyses.
Immunophenotyping by CyTOF
Many of the projects in the Center involve the single-cell data from mass cytometry (CyTOF). We apply various statistical methods to study the immunophenotypes of individuals with different atopic diseases, as well as the changes that take place during oral immunotherapy treatment for food allergies.
High-throughput sequencing analysis
In the quest to infer complex multifactorial diseases, we are utilizing sequencing technologies such as RNA-seq, methyl-seq, ATAC-seq to dissect the biology of asthma and allergies. We are constantly refining computational strategies to analyze and identify biomarkers associated with clinical outcomes in patients.
T-cell receptor (TCR) repertoire analysis
The adaptive immune response depends on B and T cells recognizing and responding to various external insults, including allergens. The analysis of immune receptors and receptor repertoires allows us to study the dynamics of the adaptive immune system. In our group, we use TCR repertoire analyses to facilitate the characterization of allergen or epitope specific repertoires in food allergic individuals.
Statistical analysis of clinical data
We work with the clinical research unit of the SNP Center on statistical analyses of original clinical trial data as well as secondary analysis of stored data in the context of food allergy and other atopic diseases. One focus is on creating intuitive visualizations of the often complex results.
Post-doctoral scholar opportunity in Computational Biology at Stanford University
A post-doctoral scholar position in computational biology is available at the Sean N. Parker Center for Allergy and Asthma Research at Stanford University (http://med.stanford.edu/allergyandasthma.html) under the directorship of Dr. Kari Nadeau. Our main goal is to study and develop novel approaches for the prevention, early detection, diagnosis, and treatment of allergies, asthma and other atopic diseases.
We are seeking a highly motivated computational scientist to extend our team of medical, immunological and bioinformatical researchers. A main part of the position will be the work with mass cytometry (CyTOF) and single cell sequencing data. The position will be under the mentorship of Dr. Sandra Andorf, Director of Computational Biology at the Sean N. Parker Center for Allergy and Asthma Research.
- Ideal candidates will have a mixture of the following skills:
- Ph.D. in bioinformatics, computational biology, biostatistics, or similar (preferably obtained no more than 1 year ago).
- Programming experience is required (preferably in R or python).
- Experience in single cell data analyses and integrative multi-omics approaches is required.
- Experience in mass cytometry (CyTOF) data analysis is a strong plus.
- Familiarity with major machine learning approaches is highly desired.
- Proven track record in problem-solving skills and creative thinking.
- A background in immunology and experience working with clinical trial data will be a plus.
- Applicants must possess good communication skills and be fluent in both spoken and written English.
To apply, please send your CV, a brief statement of research interests, and contact information for three references in one PDF document to firstname.lastname@example.org.
Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.