Multi-Modality AI Post-Doctoral Researcher
The Imaging AI Lab is a startup research laboratory within the CAMAI Center of NovaGen Research, a 501(c)(3) non-profit. We focus on medical imaging AI research including modeling multi-modality and/or longitudinal data. Our focus is to create well-prepared frameworks for medical AI modeling to the medical community.
We are seeking a highly skilled and motivated Post-Doctoral Researcher to lead the development and implementation of multi-modality solutions tailored for medical data – including imaging, EHR, and -omics. This position focuses on building a multi-modality AI framework for combining and incorporating multiple different types of medical data for building accurate predictions. If you are passionate about the intersection of AI, privacy, and medical innovation, we encourage you to apply.
Key Responsibilities:
- Develop and implement deep learning models for multi-modal medical data fusion using Python and PyTorch.
- Design and execute experiments to evaluate the performance of developed models.
- Preprocess and analyze large-scale medical imaging and other multi-modal datasets.
- Implement and evaluate various multi-modal fusion strategies (e.g., early, late, and hybrid fusion).
- Develop and apply model explainability methods to understand the contributions of different modalities.
- Collaborate with clinicians, medical experts, and other researchers to define research goals and translate findings into clinical applications.
- Contribute to the development of software tools and libraries for multi-modal AI.
- Prepare and present research findings at conferences and in peer-reviewed publications.
- Maintain accurate and detailed records of experiments and results.
Qualifications:
- Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field with a strong focus on machine learning and medical imaging.
- Proficiency in Python and deep learning frameworks, particularly PyTorch.
- Proven track record in multi-modality medical AI.
- Strong background in deep learning, machine learning, and image processing.
- Experience with medical imaging data (e.g., MRI, CT, PET) and other medical data modalities including OCT, OCTA, fundus photos.
- Experience with data preprocessing, feature extraction, and model evaluation.
- Excellent programming and problem-solving skills.
- Strong communication and collaboration skills.
- Ability to work independently and as part of a team.
- A strong publication record in relevant areas is highly desirable.
Preferred Qualifications:
- Experience with model explainability and interpretability techniques.
- Experience with clinical validation studies.
- Experience with large-scale medical datasets.
- Experience with version control systems (e.g., Git).
- A desire to learn new ideas, new systems, for example multi-agent AI systems.
#INDNG
Salary Range
$85,000 - $100,000 USD
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of NovaGen's employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: info@novagenresearch.org
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
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