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Data Scientist - NIRS Signal Processing

0 years

0 Lacs

ahmedabad gujarat india

Posted:3 days ago| Platform: Linkedin logo

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Skills Required

data signal processing research assessment learning cutting technology healthcare spectroscopy algorithms extract power analysis preprocessing filtering normalization extraction engineering development optimization regression networks deployment visualization visualize model reports collaboration documentation software pipeline integrity code physics electrical python matlab optics

Work Mode

On-site

Job Type

Full Time

Job Description

Company Description

Bioscan Research aims to improve patient outcomes for traumatic brain injury via an objective assessment for early detection at the pre-symptomatic phase, utilizing a machine learning-powered NIRS device, CEREBO. This cutting-edge technology uses advanced signal processing to provide accurate and timely diagnoses, significantly enhancing patient care. By integrating machine learning with NIRS, Bioscan Research is at the forefront of innovative healthcare solutions, dedicated to improving lives.


Role Description

Data Scientist


Key Responsibilities

  1. Signal Analysis & Preprocessing:

    Process raw NIRS signals from multiple wavelengths and source-detector distances. Implement noise filtering, baseline correction, motion artifact removal, and signal normalization techniques.

  2. Feature Extraction & Engineering:

    Identify and extract relevant optical, temporal, and statistical features from NIRS data. Perform dimensionality reduction while preserving key diagnostic information.

  3. Biomarker Computation & Validation:

    Develop algorithms to compute tissue optical biomarkers (e.g., absorption, scattering coefficients, oxygenation indices). Differentiate between healthy and diseased tissue states using machine learning or statistical modeling.

  4. Algorithm Development & Optimization: B

    uild, train, and validate predictive models (e.g., regression, decision trees, random forest, neural networks) for classification. Optimize algorithms for accuracy, speed, and robustness for deployment on embedded systems.

  5. Data Analysis & Visualization:

    Perform exploratory data analysis (EDA) and visualize trends to guide feature selection and model refinement. Summarize findings in technical reports and presentations for internal stakeholders.

  6. Collaboration & Documentation:

    Work closely with clinical, hardware, and software teams to ensure end-to-end data pipeline integrity. Maintain well-documented code, version control, and reproducible workflows.


Qualifications

  • Master’s or PhD in Biomedical Engineering, Data Science, Applied Physics, Electrical Engineering, Signal Processing, or related field.
  • Strong background in biomedical signal processing (preferably optical / NIRS / spectroscopy data).
  • Proficiency in Python, MATLAB, or R for signal processing and data science workflows.
  • Hands-on experience with feature engineering, machine learning model development, and statistical analysis.
  • Familiarity with concepts like Beer-Lambert Law, tissue optics, and optical pathlength is a plus.
  • Analytical thinker with strong problem-solving skills and attention to detail.
  • Ability to work in cross-functional teams and communicate findings clearly.
  • Curious, innovative, and comfortable working in a fast-paced, research-driven environment.

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