Senior Computational Biology & Multi-Omics Scientific Advisor - MUST Have PhD - Work Remotely

There is 25% travel required for this position (travel expenses are reimbursable).

MUST have PhD in human genetics, genomics, bioinformatics, computational biology, biostatistics, epidemiology, systems biology, or a related field

MUST have minimum 5 years of experience post doctorate

Roles and 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
• 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
• 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
• coordinating with TA3 so TA1 findings point to targets that interventions can act on

Requirements:

• 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

Preferred Experience:

• 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.

Minimum degree:

• 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