Research Fellow - Diagnostic Imaging Felix Lab

Description

The Johns Hopkins University School of Medicine Department of Radiology in the Russell H. Morgan Department of Radiology and Radiological Science in Baltimore, MD is seeking a post-doc research fellow to be hired in the FELIX 2.0 laboratory (https://thefelixlab.jhmi.edu/). This is a full-time, post-doc position.  We offer a competitive salary, vacation and excellent benefits.

The FELIX 2.0 laboratory aims to change the trajectory of how pancreatic cancer is detected, how patients are evaluated, and improve outcomes. Its mission is to harness the power of artificial intelligence, help radiologists and clinicians in detecting pancreatic cancer when it could have otherwise been missed. This is an innovative way of approaching what has been a challenge for many decades. Between Johns Hopkins Medicine, the Lustgarten Foundation, and Microsoft AI for Good, the FELIX 2.0 laboratory is pooling vast resources to improve how we do things, especially considering recent advancements in AI technology.

The position will include developing radiomics and deep learning models from contrast-enhanced computed tomography images to improve the early detection of pancreatic tumors and improve patient management. Different machine-learning approaches will be compared, and models validated on data prospectively collected. The position will include working with internal and external databases. The candidate will contribute to coordinating expert interpretation and manuscript writing under supervision.

Specific Duties/Responsibilities:

• Data Curation: Collect and organize datasets along with relevant clinical information to support and drive research studies
• Radiomics Pipeline Development: Design and optimize robust radiomics pipelines for characterization of CT images.
• Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images
•  Performance Evaluation: Conduct rigorous statistical analyses to benchmark and compare the performance of diverse approaches.
• Model Assessment and Deployment: Evaluate model limitations and implement new approaches for deploying models, enhancing their generalizability and real-world applicability.
• Communication and Reporting: Prepare reports and study findings to present to PI.
• Manuscript Preparation: Author high-quality research manuscripts for publication in peer-reviewed journals.

Special knowledge, skills & abilities:

• Proficiency in programming language such as Python, C++, R and MATLAB.
• Strong theoretical understanding and practical experience in deep learning-based machine learning or natural language processing.
• Strong background in statistical modeling.
• Strong scientific writing skills.
• Expertise in medical imaging processing or previous work in collaboration with healthcare professionals will be a plus.

Qualifications

•      Master or Ph.D. in computer science, biomedical engineering, or a related field.
•    One year of experience with machine leaning, deep learning and data analysis.

Equal Employment Opportunity Statement

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting.  Not all candidates will be eligible for the upper end of the salary range.  The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Total Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

Pre-Employment Information

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Background Checks

The successful candidate(s) for this position will be subject to a pre-employment background check including education verification.

EEO is the Law:
https://www.eeoc.gov/sites/default/files/2023-06/22 088_EEOC_KnowYourRights6.12ScreenRdr.pdf

Diversity and Inclusion

The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion.

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the COVID and flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. For additional information, applicants for SOM positions should visit https://www.hopkinsmedicine.org/coronavirus/covid-19-vaccine/ and all other JHU applicants should visit https://covidinfo.jhu.edu/health-safety/covid-vaccination-information/.

The following additional vaccine requirements may apply, depending upon your campus. Please contact the hiring department for more information.

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