Develop and execute plans for the analysis & integration of multi-modal data to develop patient stratification approaches for precision neuroscience, identify novel therapeutic targets, and enable generation of innovative disease models in support of drug discovery.
Partner closely with discovery and clinical scientists to ensure purposeful interrogation of multimodal human datasets and translation of data-derived hypotheses into clinical and wet lab validation plans.
Build strong relationships with key internal and external partners to help shape academic collaborations and define the scope of research questions.
Remain current on the constantly evolving landscape of Alzheimer’s disease and the use of omics, RWE data, and AI/ML in search of innovative approaches to derive biological insights that could accelerate and prioritize drug discovery.

PhD in neuroscience, computational biology, bioengineering, biostatistics, or a related field, completed within the past 3 years is required.
Extensive hands-on expertise in analyzing and integrating multimodal data, such as clinical, molecular, digital health and imaging data from patient cohorts is required.
Proficiency in R, Python, or similar programming languages is required.
Proven track record of scientific contributions in this field with first author publications is required.
Ability to clearly communicate technical work to a diverse audience is required.
Background and experience working in Neurodegeneration, and particularly Alzheimer’s disease, is preferred.
Experience analyzing multi-omics data is preferred.
Familiarity with machine learning and state-of-the-art AI methodologies is preferred.

Postdoctoral Researcher, Omics & Multimodal Data Integration, R&D Neuroscience, Data Science & Digital Health

Key skills