Note: The job is a remote job and is open to candidates in USA. Strategic Analysis, Inc. is hiring a Multi-Factor Analysis SETA to provide technical guidance and oversight for autism research focused on factors shaping different developmental and health trajectories. The role advises on study design, measurement, data handling, analysis, project goals and budgets, and coordination of data and findings across projects.
Responsibilities
- Provide internal subject matter expertise on how to characterize the factors behind different autism trajectories. These include genetics and epigenetics, metabolomics, immune profiling, the microbiome, environmental exposures, family factors, and developmental history. The program's starting idea is that nonlinear interactions among these factors shape different developmental, health, communication, and functional outcomes (ARPA-H)
- Give insight on whether proposed approaches are conceptually and technically sound:
- Study design: cohort design, sample size, and statistical power
- Measurement: assay and measurement choices, and batch effects
- Data handling: combining data from different sources, and quality control
- Analysis: reproducibility, and statistical methods for gene-environment and other multi-factor interactions
- Scope: any justifiable way of measuring a person's biological state is in scope, including neuroimaging and electrophysiology. Characterization is focused on humans, not model systems such as organoids (ARPA-H, n.d.-b)
- Help set goals, expectations, and budgets for TA1 projects, including milestones for generating, harmonizing, and sharing data
- Help review and oversee funded TA1 projects, including:
- Coordinating with TA2 so TA1 data and features can feed the federated, privacy-preserving modeling platforms (ARPA-H)
- Coordinating with TA3 so TA1 findings point to targets that interventions can act on
Skills
- Experience in human genetics/genomics or other 'omics research (e.g., sequencing, epigenomics, transcriptomics, proteomics, metabolomics, microbiome), covering both how the data are generated and how they're analyzed
- Experience with computational methods for high-dimensional biological data: bioinformatics, statistical genetics, data science, computational modeling, and/or machine learning
- Experience working with large human cohort or long-term datasets that combine several data types
- Experience with budgeting and program or project management
- PhD (or MD/PhD) in human genetics, genomics, bioinformatics, computational biology, biostatistics, epidemiology, systems biology, or a related field. A master's degree with substantial relevant research experience may be considered
- Ability to obtain HHS Public Trust
- Minimum five years of experience post-doc
- Genetics or biology research on autism or other neurodevelopmental conditions
- Familiarity with large autism and population datasets (e.g., SPARK, Simons Simplex Collection, MSSNG, ABCD, All of Us)
- Environmental epidemiology or exposome science; immunology; metabolism; gut-brain or microbiome research
- Methods for causal inference and interactions (e.g., Mendelian randomization, gene-by-environment modeling, polygenic scores, multi-omic integration, subtyping or clustering patients by trajectory)
- Neuroimaging or EEG analysis
- Data standards, governance, and privacy for genomic data, including FAIR principles, GA4GH standards, consent, and assent for minors, and returning results to participants
- Engaging communities in genetic research, and awareness of autistic community perspectives on it
- Lived experience of autism is a plus
- Disclosure is voluntary and not required
Benefits
- Position is remote.
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