Postdoctoral Fellow-MSH-30035-389

Title: Postdoctoral Researcher (Systems & Computational Neuroscience)

Department: Neuroscience

Physical work location: 1470 Madison Ave, 10th Floor, New York, NY, 10029

Name PI or Supervisor: Roberto Gulli roberto.gulli@mssm.edu

347-429-3453

Web link to Lab: https://gullilab.com

Web link to Department:https://icahn.mssm.edu/about/departments-offices/neuroscience

Administrative Contact: Jannell Marevanhema, Kayla <kayla.J.Marevanhema@mssm.edu>

Details of Research Project: 

How do populations of neurons encode abstract rules and spatial maps to support cognition? Our lab addresses this challenge by combining large-scale electrophysiology with advanced computational modeling to decipher the "representational geometry" of learning and memory . This project focuses on analyzing high-dimensional neural datasets recorded from the hippocampus and prefrontal cortex during complex virtual reality tasks. You will work at the nexus of experiment and theory, applying analytical frameworks to reveal how neural codes evolve during complex behaviors and how they are modulated by interventions like deep brain stimulation.

 

Technical Duties: (include any protocols)

You will lead the computational modeling and analysis of large-scale, high-dimensional neural datasets, working closely with experimentalists to design hypothesis-driven tasks that probe the limits of neural computation. Your responsibilities will include:

• Developing and applying innovative analysis pipelines for high-dimensional neural data (e.g., dimensionality reduction, representational geometry analysis, decoding) from simultaneous recordings of thousands of neurons 

• Collaborating with leading theoretical neuroscientists at Mount Sinai (e.g., Dr. Evan Schaffer) and Columbia University (e.g., Dr. Stefano Fusi) to refine computational models of learning and decision-making.

• Modeling the effects of neuromodulation (DBS) on network dynamics and learning rates to predict therapeutic outcomes.

• Contributing to the open-science community by developing and sharing robust analysis code and tools (e.g., GitHub, Neurodata Without Borders).

• Presenting your findings at international conferences (e.g., Gordon Research Conference, Society for Neuroscience) and preparing manuscripts for high-impact publications

Educational and other Requirements for the position:

• A PhD in Neuroscience, Biomedical Engineering, Psychology, Electrical Engineering, or a related field.

• Proficiency in coding (MATLAB or Python) for data acquisition and analysis.

• A strong interest in bridging the gap between basic circuit mechanisms and translational applications.

 

Experience Required:

• Laboratory experience working in behavioural neuroscience, prefereably with nonhuman primates

• Analysis of behavioural and neural datasets

• Proficiency in coding (C#, Arduino, bash)

 

Goals/Outcomes of the Research Project: 

• Mechanistic Understanding: Elucidate the circuit-level mechanisms by which DBS-f alters neural representations in the hippocampus and prefrontal cortex to improve learning and memory.

• Therapeutic Optimization: Establish a framework for predicting and explaining the variable efficacy of DBS treatments, paving the way for optimized clinical protocols.

• Career Advancement: Produce high-quality datasets leading to first-author publications in top-tier journals and support the fellow’s transition to an independent research career.

• Technological Innovation: Advance the use of large-scale recording technologies (Neuropixels) combined with neuromodulation in awake, behaving primates

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