Computational Neuroscience Research Fellow

1 week ago

Boston, Massachusetts, United States InsideHigherEd Full time

Position Overview

The main goal of this position is to create groundbreaking computational strategies that enhance our comprehension of brain impairments associated with preclinical Alzheimer's disease. The datasets utilized encompass speech acoustic and kinematic recordings, EMG, EEG, neuropsychological evaluations, clinical and neurobiological information, as well as neuroimaging data. The postdoctoral fellow will engage in various facets of data acquisition and will identify and modify state-of-the-art machine learning methodologies to encode and categorize subtle, yet potentially significant, patterns in neural and speech time-series gathered from multiple anatomical sites.

Key Responsibilities

  • 30%: Innovate advanced techniques for the integration of diverse data types (acoustic, kinematic, EMG, EEG, neuroimaging, and FlexNIRS) through machine learning. The candidate must demonstrate proficiency in handling neuroimaging datasets, including all requisite preparatory steps to ensure data integrity, to conduct innovative analyses and prepare manuscripts for publication.
  • 30%: Develop signal processing techniques for feature extraction, characterizing, and correlating neuroimaging data with speech acoustic and kinematic signals.
  • 20%: Oversee the simultaneous collection of speech and neuroimaging data from older adult participants, ensuring proficient use of equipment while effectively liaising with both study participants and the research team.
  • 10%: Prepare and preprocess data for research assistants and study personnel.
  • 10%: Contribute preliminary findings to grant proposals.

Supervisory Duties

  • Will mentor and indirectly supervise 1 full-time equivalent (FTE).

Qualifications

  • Ph.D. in engineering, neuroscience, computer science, speech and language sciences, computational linguistics, or a related discipline by the start date.
  • Strong programming capabilities in scripting languages such as MATLAB, Python, R, or similar environments.
  • Experience with Natural Language Processing (NLP), Machine Learning (ML), and Data Science.
  • Excellent communication and research writing skills.
  • Familiarity with data visualization and statistical modeling/analysis.
  • Proven track record of scholarship as demonstrated by peer-reviewed publications and/or conference presentations.

Skills and Abilities

  • Exceptional computational and scientific writing skills.
  • Proficiency in MATLAB or Python.
  • Experience with distributed computing.
  • Ability to communicate effectively in a professional setting.
  • Enthusiasm and capability to tackle technical and computational challenges.
  • Strong organizational skills.
  • A collaborative team player.

Working Environment

  • Computational tasks will be performed in an office setting, utilizing a laptop and/or a Linux workstation.
  • Data collection will occur in a soundproofed room or in a magnetic resonance imaging bay.

Training Expectations

It is anticipated that the postdoctoral fellow will arrive with the computational expertise necessary for scientific contributions. However, familiarization with the specific data and neuroimaging processing software is expected to take up to 2 months. Learning to operate the MRI scanner, EEG equipment, and speech recording apparatus will require approximately 4 months.

About the Institution

The institution is a prominent graduate school that offers entry-level and post-professional programs across various health-related fields. It integrates classroom learning with research and clinical experience, granting doctoral and master's degrees, as well as certificates of advanced study. The institution is committed to fostering a supportive and inclusive environment and actively engages in initiatives aimed at addressing systemic racial injustice and promoting diversity and inclusion.

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