Now is an exciting time for biomarker research for Alzheimer's disease (AD), especially in the context of personalized treatment strategies. Two lines of research development drive this. First, recent technological advances have enabled the ultrasensitive detection of plasma proteins as potential diagnostic and prognostic tests for AD. These tests can accurately detect AD pathologies in the brain of patients. Second, the recent exciting data supports anti-amyloid immunotherapy and its efficacy in reducing amyloid plaques in the brain and potentially slowing down cognitive decline. However, the causes of AD are multifactorial and heterogeneous. Factors outside the brain and peripheral are essential for broadening our perspective and understanding of AD pathophysiology and developing precision medicine multimodal treatment strategies for patients.
Our lab focuses on precision medicine and the vascular contributions of peripheral proteins and lipids as biomarkers in AD. Our investigation of lipid-related pathways might lead to plasma lipids as therapeutic targets for treating AD and related dementias. We are looking for a highly motivated researcher with bioinformatics and biostatistical skills in omics data to apply their knowledge to answer relevant biological questions in the context of Alzheimer’s disease. This person will be primarily responsible for data management, cleaning and quality controlling datasets and preparing them for analysis, analyzing large-scale proteomics and other “omics” data using programming languages (e.g., R), and correlating data with outcomes available in clinical trials and epidemiological studies. This person will also assist the Principal Investigator with data interpretation and manuscript preparation. This position is an excellent opportunity for an entry-level researcher with an advanced coursework to gain more real-life research experience.
Responsibilities • Prepare data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources • Analyze large-scale proteomics and other “omics” data to answer research questions, including data visualization, statistical analysis, machine learning, and data mining • Organize and automate project steps for data preparation and analysis • Identify patterns in the data with outcomes available in clinical trials and epidemiological studies • Assist with data interpretation and manuscript preparation
All required qualifications must be documented on application materials
Required Qualifications: • Bachelor’s degree in science or engineering and at least two years of relevant experience or a combination of education and experience to equal six years. • Experience managing datasets and preparing analysis • Excellent organization and attention to detail. • Excellent communication skills – verbal and written.
Preferred Qualifications: • Experience with bioinformatics and/or biostatistics.
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.