Scientist - Neuromodulation Anatomy: Multimodal Data Integration

The Allen Institute accelerates science for a healthier world through large-scale research designed to answer some of the most complex questions in biology. Our multi-disciplinary teams generate foundational knowledge, tools, and data to understand how our brain, cells, and immune system work. We share our work openly so others can build on it, move faster, and ask bigger questions. We drive discovery forward and create new possibilities for improving human health.

The goal of the Neural Dynamics accelerator is to understand how the brain generates flexible behavior. We aim to uncover the algorithms—implemented by dynamics in brain-wide neural circuits— that allow animals to build internal models, process information, and choose actions.

We are seeking an exceptional scientist to join the Neuromodulation, specifically to create a comprehensively map of the structural organization of neuromodulatory systems in the mouse brain. Neuromodulators such as nor epinephrine, serotonin, dopamine, and acetylcholine are released by small populations of neurons yet exert widespread effects on neural dynamics and behavior. Recent research has begun to reveal substantial diversity among neuromodulatory neurons.

Uncovering the structural, molecular, and functional relationships among these cell types is critical to understanding neuromodulation.

The project brings together transcriptomic, morphological, and connectivity datasets being generated at the Allen Institute to uncover the organizational principles of neuromodulatory systems. The scientist will work closely with experimentalists and develop and apply advanced statistical, computational, ML and AI methods to analyze multimodal data including single cell transcriptomics, single neuron reconstructions, input and output connectivity, and in vitro and in vivo physiology.

A central biological question is how neuronal properties measured across these modalities align to define functionally relevant cell types. This role offers substantial scope to think deeply about this question and develop conceptual and quantitative frameworks to address it. The scientist will lead the project’s multimodal integration and analysis efforts in close collaboration with experimental and computational teams across the Allen Institute.

They will be expected to produce foundational knowledge and openly shared datasets on the structural organization of neuromodulation. For an example of this approach to integrating multimodal neuronal data, see Su et al. Nature 2026.

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Essential Functions

• Help lead a research project to establish foundational knowledge of mammalian neuromodulatory cell types
• Develop and devise conceptual and quantitative frameworks for understanding how neuronal properties measured across modalities relate to cell type identity and function
• Conduct in-depth analyses and modeling of neuronal morphology using single neuron reconstruction data
• Develop and apply methods to integrate transcriptomic, morphological, and connectivity data
• Collaborate closely with experimentalists and computational scientists to advance shared research goals
• Communicate project progress frequently and present findings to internal stakeholders and…