Bioinformatics Specialist II
Job description
Bioinformatics Specialist II
- (3235692)GENERAL SUMMARY/ OVERVIEW STATEMENT:
The Harvard Aging Brain Study group is focused on the statistical prediction and longitudinal modelling of the earliest stages of pathological and cognitive changes in preclinical Alzheimer’s disease. Our goal is to improve the detection of the preclinical stages of disease and inform AD prevention trials using multi-modal neuroimaging, as well as a vast array of cognitive, behavioral, lifestyle, biofluid measurement of Alzheimer’s disease proteins, as well as genomics and transcriptomic information. The Harvard Aging Brain Study Data and Informatics team provides statistical, informatics, neuroimaging and data management support, consultation, and didactics to Harvard faculty, postdoctoral fellows and research assistants who are affiliated with the Harvard Aging Brain Study.
The Bioinformatics Specialist II is part an interdisciplinary team working in Alzheimer’s disease, with a particular focus on the integration of multiple, large datasets including genomics scale next-generation sequencing data, single cell RNAseq and epigenetics applied to cognitive and neuroimaging data from secondary data sources. Alongside a primary analytic focus of this role, the Bioinformatics Specialist II handles the acquisition and maintenance of Data Use Agreements, interfacing with the data management members of the Data and Informatics team, quality assurance of these data, development, and implementation of data harmonization pipelines.
This is a vibrant research environment comprising clinical, neuroimaging, and computer scientists that have access to large data repositories. This position will join the analyst side of the Data and Informatics team and will report directly to the Data Analytics Manager. The team is located at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School – a world class center for biomedical neuroimaging.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
- Acquisition and quality assurance of large secondary data sources
- Setting up and maintaining Data Use Agreements for accessing data sources
- Developing implementing and maintaining sophisticated data harmonization protocols and code across multiple modalities (neuroimaging, cognition, behavioral data)
- Implementation of statistical analysis plans to produce results for eventual publication and conference dissemination for other lab personnel
- Integration of Alzheimer’s disease genome, transcriptome and epigenomic data with other AD endophenotypic data: analysis and pipeline development for whole blood and single cell sequencing platforms (RNAseq, ATAC-seq).
- Applying and developing scripts for the analysis of next-generation sequencing data (DNA, RNA ChIP-seq, ATAC-seq), single cell data sets, developing integrated data visualization and analysis tools and producing robust software solutions.
- Development and/or implementation of new analytic tools/statistical packages and providing training and assistance to other researchers on the use and function of analytic and visualization tools (predominantly using R software package)
- Researching, assessing, and implementing sophisticated statistical models (functional data analysis, general additive modeling, structural equation modeling, causal inference, nonlinearity of change over time (through change points, polynomials, splines)) and approaches using R
- Develop data analysis strategies and apply them to preclinical Alzheimer’s data sets, critically review and analyze results, communicate results to behavioral neurologists, neuropsychologists and neuroimagers
- Interfacing with data management side of the Data & Informatics team through the loading of external data into the clinical database using SQL code. To be able to receive, track and load the external data into the database system and reconcile this data with other clinical data. To interact with suppliers of external data in negotiating format and method of transfer.
- Liaise with external Principal Investigators and their teams who are collaborating on co-funded NIH research proposals
- Developing and maintaining best practice guidelines and Standard Operating Procedures for R programming and report production within the D&I team
- Liaise with researchers to aid in the development and implementation of their statistical data analytics and visualizations in service of research aims.
- Rapid assembly and manipulation of datasets for analysis.
- Provide consultation and drafting of methods and results sections for manuscripts in collaboration with researchers.
SKILLS/ABILITIES/COMPETENCIES REQUIRED:
- Advanced knowledge of statistical testing and multivariate modeling (i.e., linear mixed models, linear regression, functional data analysis, general additive modeling, structural equation modeling, data reduction techniques).
- Advanced knowledge of data visualization.
- Familiarity with data harmonization approaches.
- Familiarity with genomics and transcriptomic analysis.
- Strong programming skills in R software package and willingness to learn other programming languages as necessary.
- Advanced computer skills, with the ability to manipulate large and varied datasets (ideally in SQL).
- Very detail-oriented and highly organized.
- Ability to work independently and as part of a team.
- Strong problem-solving skills.
- Ability to manage multiple studies/projects and provide mentoring to Data Analyst I and/or Data Analyst II staff, as needed
- Ability to prioritize work, operate under tight deadlines, and meet deadlines.
- Level of responsibility and maturity to work under pressure and meet the requirements of a clinical research neuroscience laboratory.
- Resilient, collaborative, flexible and innovative.
- Strong written communication and presentation skills.
- Exposure to other statistical packages is of interest but not essential (e.g. MATLAB, MPlus, SAS, etc).
EDUCATION:
Master’s Degree required. Training must be in the fields of biostatistics, applied mathematics or statistics. Individuals without formal training in these areas, but with the requisite experience and desired core skills will also be considered.
EXPERIENCE:
5+ years of work experience is required. Experience through graduate research projects is applicable.
WORKING CONDITIONS:
In-person or hybrid. Fully remote will be considered for the right candidate.
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