The Nead group is based in the departments of Epidemiology (primary) and Radiation Oncology (secondary). The Nead group currently has a funded open postdoctoral fellow position to study the association of somatic (acquired) genetic changes with cancer development, cancer treatments, and cancer outcomes. Developing research has demonstrated that normal tissues commonly acquire genetic changes and that these acquired variants may have implications for health and treatment outcomes. Our group studies acquired genetic changes in normal tissues (e.g. breast tissue, blood) and how these acquired genetic changes are influenced by cancer treatments (e.g. chemotherapy and radiation therapy), how they impact cancer outcomes (e.g. survival, toxicity), and how they are modulated by cancer risk factors (e.g. age, obesity, smoking). We have ongoing projects available for a postdoctoral fellow to take the lead on as well as ample opportunity and resources for the fellow to explore new avenues of independent research in genetics and genetic/molecular epidemiology. The Nead group has significant computational resources, wet laboratory space, access to a wide array of clinical samples and data, and the support of a full-time computational scientist, research analyst, and laboratory research assistant. Additionally, we support a rich learning environment with multiple active trainees from the masters to MD and/or PhD level. This position reports to Kevin T. Nead, MD, MPhil with ample opportunity for co-mentoring from other faculty collaborators.
- Gain and advance skills in the analysis of genotype and sequencing data using advanced sequencing techniques and bioinformatic approaches
- Gain or advance skills in the analysis of clinical data as it relates to patient level genetics and genomics
- Learn to develop independent lines of research
- Advance skills in study design, data analysis and interpretation
- Develop skills in fellowship application and grant writing in order to advance career to the desired next step
PhD and/or MD or equivalent with a degree and/or significant experience in molecular/genetic epidemiology, computational biology, bioinformatics, data science, or a related field. A computational background and proficiency in at least one scripting language (e.g., R, Python) and basic knowledge of biostatistics are required. Experience working with genotyping and/or sequencing data are desired. Proficiency in spoken and written English is highly desired.
Dates or Training Schedule:
The appointment is immediately available for a full-time position. Two-year minimum commitment with additional commitment reviewed annually.
Per NIH postdoctoral fellow stipend policy.
Please send a Cover Letter, CV, and contact information of three (3) Referees to email@example.com with the subject line: “Postdoc-Application – *Applicant’s Name*."
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