Machine Learning Postdoc Fellow - (3275216)
Our laboratory applies computational and machine learning methods to investigate the impact of seizures and abnormal brain activity on outcomes in pigs with cortical impact. Our goal is to understand pathological correlates of epilepsy and traumatic brain injury. Analysis of datasets (including video–EEG telemetry, intracellular Chloride, among others) is central to these efforts.
Specific efforts focus on developing methods for automatically classifying the semiology of pigs in video monitoring as they undergo the development of epilepsy and understanding the relationships between any abnormal behaviors and time after injury or the change in seizure frequency. Efforts will particularly focus on using supervised machine learning approaches including training artificial neural networks via open source software such as Keras, Tensorflow, DeepLabCut, SimBA, TREBA etc. or unsupervised learning methods, heuristics, and other algorithms to learn patterns, fit and extrapolate from models, and process large datasets of video frames.
The person will interact with staff in other lab’s such as Sydney Cash’s lab, Kevin Staley’s lab, and Kyle Lillis’ lab.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
The machine learning engineer will work and mentor a team of researchers in searching for patterns hidden in large data sets for research in neurology. The machine learning engineer will be responsible for data from the electronic data repository, including EEG, video, and peripheral blood biomarkers. The machine learning engineer will develop unique algorithmic approaches for analysis of data and supervise and mentor a team of research staff. Responsibilities will include:
Any additional skills are a plus including:
Parallel computing, command prompt, working with GPUs, supercomputing, video software (e.g. ffmpeg), SQL, large language models, MATLAB, PHP, or other additional languages, hardware knowledge, advanced understanding of kernel, neurobiology knowledge, et
EDUCATION:
PhD in a relevant discipline such as: computer science, math, computer engineering, statistics, cognitive science, electrical engineering, bioengineering, data science, etc.
EXPERIENCE: Specify minimum creditable years of experience and clearly indicate if preferred or required
Minimum of 2 years of relevant experience required.; Knowledge of some Computer Science/Engineering concepts required.
FISCAL RESPONSIBILITY:
No budgetary responsibility but will need to design projects and identify equipment for projects within a budgetary scope and in liaison with a staff assistant performing purchase orders.
WORKING CONDITIONS:
Work will be performed in CNY Building 149 and some work on and in laboratory space on the MGH main campus.
EEO Statement Massachusetts General Hospital is an Equal Opportunity Employer. By embracing diverse skills, perspectives and ideas, we choose to lead. Applications from proted veterans and individuals with disabilities are strongly encouraged.
: MA-Boston-MGH Main Campus
:
MGH Main Campus
55 Fruit Street
Boston 02114
: MD/PHD/Fellows/ PostDocs
: Massachusetts General Hospital(MGH)
: Full-time
Standard Hours: 20
: Day Job
: Regular
Recruiting Department: MGH Neurology Research
: Jan 26, 2024
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