Job ID: 3055043
Job date: 2018-01-05
End Date:
Company : Massachusetts General Hospital Country : Role : Other
Job date: 2018-01-05
End Date:
Company : Massachusetts General Hospital Country : Role : Other
Job Description:
We are seeking a highly motivated individual to work collaboratively with a team of clinicians, computational engineers, and research coordinators. The incumbent will develop and employ machine learning tools for the detection of hippocampal epileptiform activity. The incumbent must possess a strong programming background (MATLAB, Python, C++, Linux OS), expertise in big data (including pre-processing and cleaning big data sets), expertise in machine learning (particularly deep learning, including experience with TensorFlow, Keras), a strong foundation in signal processing, prior experience working with neurophysiologic data (including scalp EEG and intracranial EEG), and the drive and enthusiasm to learn about clinical neuroscience and patient-centered research. PRINCIPAL DUTIES AND RESPONSIBILITIES: This position involves a wide range of responsibilities, including: ·Technical set-up and hands-on equipment responsibilities, including hardware and software maintenance on deep learning computers ·Management of a large database of neurophysiologic data. ·Pre-processing of big data sets of neurophysiologic recordings. This includes: o Ability to visually screen the data for artifact identification and data selection o Data cleaning, transformation, feature extraction and feature selection o Optimization of memory requirements, allocation, and efficient usage in implementation of the above tasks ·Software development and code management for development and optimization of deep learning algorithms for detection of epileptiform activity. This includes: o Design, selection, and optimization of complex neural network architectures, including combinations of convolutional networks and recurrent networks o Hyperparameter optimization and regularization techniques to improve the performance of deep neural networks o Design and implementation of tools to assess learning performance and generalizability of deep learning algorithms in real-time o Development of software deliverables that implement fully trained deep learning algorithms for practical use by clinicians on clinical data .Provide appropriate training, mentorship, and assistance with trouble-shooting code to research coordinators and students in the lab working on signal processing and machine learning projects
Additional Info:
The MGH Epilepsy Service and the MGH Cortical Physiology Laboratory are leaders in developing and applying computational and engineering techniques in combination with clinical neurophysiology recordings, to improve the diagnosis, monitoring, and treatment of people with epilepsy. Major initiatives include efforts to develop computational algorithms that can non-invasively diagnose epilepsy and monitor epileptiform activity in clinical situations that currently require invasive monitoring. [Click Here to Access the Original Job Post]
We are seeking a highly motivated individual to work collaboratively with a team of clinicians, computational engineers, and research coordinators. The incumbent will develop and employ machine learning tools for the detection of hippocampal epileptiform activity. The incumbent must possess a strong programming background (MATLAB, Python, C++, Linux OS), expertise in big data (including pre-processing and cleaning big data sets), expertise in machine learning (particularly deep learning, including experience with TensorFlow, Keras), a strong foundation in signal processing, prior experience working with neurophysiologic data (including scalp EEG and intracranial EEG), and the drive and enthusiasm to learn about clinical neuroscience and patient-centered research. PRINCIPAL DUTIES AND RESPONSIBILITIES: This position involves a wide range of responsibilities, including: ·Technical set-up and hands-on equipment responsibilities, including hardware and software maintenance on deep learning computers ·Management of a large database of neurophysiologic data. ·Pre-processing of big data sets of neurophysiologic recordings. This includes: o Ability to visually screen the data for artifact identification and data selection o Data cleaning, transformation, feature extraction and feature selection o Optimization of memory requirements, allocation, and efficient usage in implementation of the above tasks ·Software development and code management for development and optimization of deep learning algorithms for detection of epileptiform activity. This includes: o Design, selection, and optimization of complex neural network architectures, including combinations of convolutional networks and recurrent networks o Hyperparameter optimization and regularization techniques to improve the performance of deep neural networks o Design and implementation of tools to assess learning performance and generalizability of deep learning algorithms in real-time o Development of software deliverables that implement fully trained deep learning algorithms for practical use by clinicians on clinical data .Provide appropriate training, mentorship, and assistance with trouble-shooting code to research coordinators and students in the lab working on signal processing and machine learning projects
Qualifications
SKILLS/ABILITIES/COMPETENCIES REQUIRED: Required: ·Strong analytical skills and the ability to identify problems and perform independent problem-solving ·Desire, motivation and proven ability to work in multidisciplinary teams and within a fast-paced environment. ·Excellent written and oral communication skills, including the ability to communicate technical concepts to a non-technical audience ·Ability to provide appropriate training and instruction to junior lab staff for initial signal processing and machine learning projects. ·Ability to multi-task and work independently to solve problems ·Attention to details with strong ability to interact effectively with many different people throughout the institution including patients, doctors, nurses, grant administrators, and, most importantly, other members of the IT departments within Partners Healthcare. EDUCATION: Master’s degree in electrical engineering, computer science, biomedical engineering, or a related field, with expertise with signal processing and machine learning EXPERIENCE: Required: ·Computer science, electrical engineering, or biomedical engineering background with expertise in MATLAB, Python, C++, Linux ·At least one year of hands-on practical experience in developing machine learning applications, particularly deep learning applications ·Expertise in signal processing, particularly for neurophysiologic signals (EEG, intracranial EEG) Preferred: ·Practical experience with management of big data ·Experience with high-dimensional biomedical data and technology platforms SUPERVISORY RESPONSIBILITY (if applicable): None, but will work within a team of physicians, clinical research coordinators, post-docs, graduate students and scientists. WORKING CONDITIONS: Work will be performed in the MGH Cortical Physiology Laboratory space on the MGH main campus.Requeriments :
Skills :
- Lunix/Unix
- Machine Learning
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in Matlab
- Software Design
Areas :
Additional Info:
The MGH Epilepsy Service and the MGH Cortical Physiology Laboratory are leaders in developing and applying computational and engineering techniques in combination with clinical neurophysiology recordings, to improve the diagnosis, monitoring, and treatment of people with epilepsy. Major initiatives include efforts to develop computational algorithms that can non-invasively diagnose epilepsy and monitor epileptiform activity in clinical situations that currently require invasive monitoring. [Click Here to Access the Original Job Post]