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Open Postdoctoral position, faculty mentor Frank Longo

Important Info

Faculty Sponsor (Last, First Name): 
Longo, Frank
Stanford Departments and Centers: 
Neurology & Neurological Sci
Postdoc Appointment Term: 
Appointment will be initially for one year, with an expectation of renewal for a 2nd on satisfactory performance.
Appointment Start Date: 
July 1, 2020
How to Submit Application Materials: 

To apply, please submit the required aplication materials to Frank Longo, MD, PhD at

The Opportunity
The Longo laboratory at the School of Medicine at Stanford University seeks a Ph.D. researcher for a postdoctoral position in interdisciplinary research with expertise in data science and biological sciences, preferably neuroscience. Post-doctoral fellows will straddle the borders of data science and biology to apply data science methods to human Alzheimer’s databases with the goal of increasing the applicability of drug discovery trials in Alzheimer’s disease mouse models. The ideal candidate will have earned a PhD in either a methods or applied discipline with demonstrated skills and experience in one of the other complementary areas (as examples: a PhD in statistics with applications to biology, or a PhD in biology with extensive use of machine learning). His/her research results will be published in technical reports, open-source software, peer-reviewed journals as well as presented at scientific conferences. Ideal candidates will also have experience and interests in building community, teaching and training, and leadership with strong communication skills.
Scientific background
Recent Alzheimer’s trials have failed likely because the treatments targeted single processes such as the accumulation of amyloid. Within this category of brain disease however, multiple processes are likely to present including accumulation of amyloid, toxic forms of the tau protein, neuro-inflammation and indeed, degeneration related to aging itself. The Longo Laboratory has been successful in discovering novel drug-based approaches for Alzheimer’s disease and other dementias that simultaneous target multiple degenerative processes including those related to amyloid, tau, inflammation and aging. One drug developed in our laboratory is currently undergoing testing in an NIH-supported human phase 2a Alzheimer’s trial. Other candidate drugs are in various stages of development ranging from first tests using neurons grown in tissue culture dishes to mouse testing. However, a major challenge for developing neurological therapies is the translation of successful testing in mice to human trials. With the large transcriptomics datasets that we and others are generating, we now have the opportunity to understand how these drugs affect our Alzheimer’s mice and thereby prioritize mouse therapy analyses according to human relevance, and thus more likely for success in human trials.
Duties include
- Consult with investigators on appropriate statistical approaches to data analyses; assist in study design and proposal development (power calculation, sample size estimate)
- Develop and implement protocol for quality control (Data cleaning and preprocessing)
- Select appropriate statistical tools for addressing a given research question (Identify or develop the most appropriate statistical tests/tools based on experimental design to address research question)
- Create analytic files with detailed documentation (Write R scripts and corresponding information for reproducible research)
- Implement data analysis through statistical programming (Create analysis pipeline using R and when needed other languages / softwares)
- Summarize findings orally and in written form, present results for investigators (Disseminate findings within and outside the Longo lab group)
- Participate in the preparation of papers for publication (generate figures; write corresponding methods and results sections; provide insights for discussion of the results)

Required Qualifications: 
  • Recent PhD with experience in a complementary field(s), preferably biology and/or neuroscience.
  • Excellent knowledge of RNA sequencing and statistics (eg a PhD in statistics with applications to biology, or a PhD in biology with extensive use of machine learning)
  • Excellent knowledge of R and Bioconductor
  • Excellent verbal and written communication and presentation skills necessary to author scientific reports, publications, invited papers, and to deliver scientific presentations, and/or meetings .
  • Experience collaborating effectively with a team of scientists of diverse backgrounds.
Required Application Materials: 
  • Applicants should submit their (1) curriculum vitae, (2) publication/software list, and (3) two-page letter of intent detailing a proposed research project.
  • Applicants should arrange to have two letters of reference submitted to the below email with the subject line: Reference Letter for <applicant's name>.


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.