About nFerence:
At nFerence Labs, the “Google of Biomedicine” (see nference.ai/media), we are building a large-scale computational platform to reverse engineer biology. By combining AI and high-performance computing, we connect clinical observations (phenotypes) with DNA-level phenomena (genotypes) to accelerate drug discovery and enable early disease diagnosis.
We collaborate with leading medical research institutions and work with diverse patient data such as clinical text, lab results, medical images, and ECGs. Our affiliated company, anumana.ai, focuses on AI-driven cardiology solutions and clinical studies for cardiovascular algorithms.
Our team brings together computer scientists, biologists, and medical experts (MDs and PhDs) from top universities, creating a fast-paced and innovative environment to solve real-world biomedical challenges.
Qualifications:
MBBS or above from a reputed institution in India
Requirements:
1 - 3 years of relevant clinical / research / healthcare industry experience
Strong understanding of the nuances of medicine about patient care (a broader understanding of Cardiology/ Internal Medicine/ ICU is preferred)
Strong understanding of any of the programming languages Eg: Python or R
Basic interpretation of ECGs
Strong interest in research and product development
Basic understanding of Python and SQL (Optional)
Basic understanding of biostatistics (Optional)
Job Description:
Working near the software and data science team in developing deep learning models based on ECG inputs
Tagging the dataset with high-level accuracy for the development of AI models
Curating disease codes, procedure codes, lab codes, etc either from external sources or from internal data as and when required.
Reviewing the patient notes in EHR as required
Develop clinically sound and scientifically relevant technical user stories by utilizing the apps that are already developed or under development.
Benefits:
Chance to be a permanent part of “Google of biomedicine” as recognized by the Washington Post
Work with some of the brilliant minds of the world solving exciting real-world problems through Artificial Intelligence, Machine Learning, analytics, and insights through triangulating unstructured and structured information from the biomedical literature as well as from large-scale molecular and real-world datasets.
Chance to be a contributing author in research publications.
