Department of Public Health Sciences Division of Biomedical Informatics Seeks a Faculty Member PhD Biostatistician With Experience in Molecular Data Analysis to Join Our Women’s and Children’s Health Research Group

Department of Public Health Sciences Division of Biomedical Informatics Seeks a Faculty Member PhD Biostatistician With Experience in Molecular Data Analysis to Join Our Women’s and Children’s Health Research Group

  • Detroit, United States
Department of Public Health Sciences Division of Biomedical Informatics Seeks a Faculty Member PhD Biostatistician With Experience in Molecular Data Analysis to Join Our Women’s and Children’s Health Research Group
Job description

The Department of Public Health Sciences (PHS) Division of Biomedical Informatics is seeking an open rank faculty position to support the biostatistical needs of projects with a molecular focus within our Women’s and Children’s Health Research Group. This group includes epidemiologists, biostatisticians, and bioinformaticians with multiple federally funded projects to study the developmental origins of human diseases (eg. childhood onset obesity and neurodevelopmental disorders), gynecological conditions and related clinical treatments, and pregnancy/birth outcomes. These studies are using innovative biospecimens (eg. baby teeth, placenta, newborn blood spots) to study the molecular (metabolomic, metagenomic, epigenetic, and transcriptomics) contributors to these phenotypes in racially and socioeconomically diverse populations. While the position is principally collaborative, applicants with a desire to develop independent principal investigator initiated research will have the opportunity to do so.

Desired skills and experience

· PhD in biostatistics/statistics or PhDs in either epidemiology or bioinformatics with significant formal statistical training (ie. master degree in biostatistics/statistics or equivalent).

· Desire to work as a collaborative biostatistical scientist in research focused on women’s and children’s health and prior experience working on such research.

· Experience with the development and application of methodology for the analysis of high-throughput “omics” data – exposure to multiple platforms and molecular types is preferred

· Experience with algorithms for quality control and production of analysis ready data from metabolomics and next generation sequencing platforms is preferred

· Expertise in statistical programming and data management; R (required); SAS (preferable); and Python and/or other scientific programing languages (preferable)

· Familiarity with software packages for “omics” data analysis

· Excellent writing skills for grant development and the preparation of scientific manuscripts

.Excellent verbal communication skills to interact with teammates, researchers, and clinical staff.

About the employer

Department of Public Health Sciences (PHS) – The Department of PHS exists within Henry Ford Health (HFH), an academic medical center consisting of five major hospitals and over 30 clinics servicing the population of southeastern and southcentral Michigan. PHS is composed of PhD and masters level epidemiologists, biostatisticians, and bioinformaticians who conduct and collaborate on population and clinical research studies to advance biomedical knowledge that will advance disease prevention, health status, and clinical care. PHS has multiple specialized area of research, including our Women’s and Children’s Health Research Group.

Division of Biomedical Informatics – Within PHS, the Division of Biomedical Informatics is composed of PhD and MS level researchers who work in teams and collaborate with epidemiological and medical researchers to design, analyze, and interpret high-throughput molecular data studies. We are involved in all areas of research from grant development and study design through analysis, and we collaborate closely with the Women’s and Children’s Health Research Group. In addition to molecular data analysis, the Division of Biomedical Informatics has expertise in the analysis of data from electronic medical records and medical images.

Areas of Research
  • Genomic Bioinformatics
  • Biostatistics
  • Gender Studies