Overview
On Site
Full Time
Skills
Health Information Management
Science
Deep Learning
Management
IT Infrastructure
Data Processing
Systems Architecture
Software Design
Problem Solving
Data Analysis
Machine Learning (ML)
Clinical Research
Clinical Trials
Network
Evaluation
Clinical Data Management
Leadership
SAP R/3
Health Informatics
Research
Database Design
Database
SQL
Artificial Intelligence
Natural Language Processing
Programming Languages
Java
Python
Data Modeling
Ontologies
Data Warehouse
Apache Hadoop
Data Lake
Analytical Skill
Writing
Publishing
Job Details
The AI Research Engineer will work closely with Health Informatics faculty in the Department of Health Information Management (HIM) and Clinical and Translational Science Institute (CTSI) to design, implement, and maintain Artificial Intelligence (AI), Natural Language Processing (NLP), and Deep Learning (DL) models for use in clinical research infrastructures. The individual will oversee and enhance IT infrastructure related to AI and clinical data processing, provide technical expertise in system architecture, software design, and IT technology selection. In addition, this individual will use advanced analytical and problem-solving skills to tackle high-scale data challenges and contribute to supporting clinical and translational research.
Data analytics skills in developing, implementing, and delivering Al, machine learning, and natural language processing projects are preferred.
The individual will design and implement the AI/NLP models in the clinical research infrastructure for the Evolve To Next-Gen Accrual to Clinical Trials (ENACT) Network to facilitate clinical and translational research.
Responsible for the implementation and deployment of AI/NLP/DL models in clinical infrastructure, the evaluation of different medical data standards including OHDSI common data model (CDM) and i2b2 CDM. In addition, the candidate will also summarize the results in scientific articles and submit to academic conferences and journals.
The candidate will communicate with several stakeholders, including CTSI leadership to understand the demands, the Pitt internal R3 office to understand the Neptune data warehouse operation, and health informatics faculties for the overall strategy.
Ability to adapt, reprioritize, and take on duties to meet needs of the clinical and translational research. - Experience and knowledge of skillsets weighted more heavily than years of experience - Experience with database design, database programming skills, SQL skills
- Experience with implementing and deploying AI/NLP models
- Expert in one or more programming languages (Java and Python preferred)
- Experience with data model design, data standards, ontology design is a plus
- Experience with data warehousing, Hadoop/data lake platform implementation is a plus
- Experience of IT platform implementation in a technical and analytical role is a plus
- Experience of writing, submitting, and publishing scientific articles
Applicants must submit cover letter, resume/CV, and 2 reference letters.
Data analytics skills in developing, implementing, and delivering Al, machine learning, and natural language processing projects are preferred.
The individual will design and implement the AI/NLP models in the clinical research infrastructure for the Evolve To Next-Gen Accrual to Clinical Trials (ENACT) Network to facilitate clinical and translational research.
Responsible for the implementation and deployment of AI/NLP/DL models in clinical infrastructure, the evaluation of different medical data standards including OHDSI common data model (CDM) and i2b2 CDM. In addition, the candidate will also summarize the results in scientific articles and submit to academic conferences and journals.
The candidate will communicate with several stakeholders, including CTSI leadership to understand the demands, the Pitt internal R3 office to understand the Neptune data warehouse operation, and health informatics faculties for the overall strategy.
Ability to adapt, reprioritize, and take on duties to meet needs of the clinical and translational research. - Experience and knowledge of skillsets weighted more heavily than years of experience - Experience with database design, database programming skills, SQL skills
- Experience with implementing and deploying AI/NLP models
- Expert in one or more programming languages (Java and Python preferred)
- Experience with data model design, data standards, ontology design is a plus
- Experience with data warehousing, Hadoop/data lake platform implementation is a plus
- Experience of IT platform implementation in a technical and analytical role is a plus
- Experience of writing, submitting, and publishing scientific articles
Applicants must submit cover letter, resume/CV, and 2 reference letters.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.