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We are seeking a highly motivated and talented postdoctoral fellow to join our Surgical Outcomes and Oncology research team in The Department of Surgery at Mayo Clinic in the field of Machine Learning and Artificial Intelligence (AI). The position is for a 2-year paid fellowship (minimum 1 year commitment) with the possibility of extension beyond 2 years based on performance and availability of funding. Fellows would work under the mentorship of Dr. Simon J. Laplante, Surgeon in Metabolic and Abdominal Wall Reconstructive Surgery and Dr. Hojjat Salehinejad, Scientist in the Kern Center for the Science of Health Care Delivery & Assistant Professor of Health Care Systems Engineering. The successful candidate will have the opportunity to work with a dynamic and collaborative research team and make significant contributions to the advancement of medical AI research.

Responsibilities:

Conduct original research in AI and related fields, including designing and implementing experiments, developing algorithms, and analyzing results.

Publish research findings in top-tier medical conferences and journals.

Collaborate with other researchers and team members to advance research goals and solve challenging problems.

Participate in the development of new research proposals and assist with grant writing.
A Research Fellow at Mayo Clinic is a temporary position intended to provide training and education in research. Individuals will train in the research program of a Mayo Clinic principal investigator. Qualified individuals will demonstrate the potential for research as evidenced by their training and peer-reviewed publications and should become competitive for national research grants. Upon background check and CCATS Executive Committee approval, Research Fellow may have patient/research subject contact directly relating to and incidental to the original research program. Proof of English proficiency is required for J-1 Short-Term Scholars, Research Scholars, Professors, Specialists, and Student Interns sponsored by Mayo Clinic.

Ph.D. in Computer Science, Electrical Engineering, or a related field with a strong emphasis on AI, machine learning, or related fields. Candidates for the training or those with without advances degrees who have prior work experience are also encouraged to apply. Surgical trainees with relevant prior experiences who are able to take time out of their training (lab years) are also encouraged to apply. 

The application is open to both clinicians, research candidates, and those in technology sector including those currently in training or have recently completed training (post-doc). The expectation at the end of the fellowship is that the fellow will be well prepared to become a leader in Healthcare AI/ML, either in the academic or biotechnology setting. 

The ideal candidate must have strong expertise in data structures and algorithms, Python programming language (including libraries such as Pandas, Scikit-learn), shell scripting, Tensorflow/PyTroch (preferred), and/or machine learning (particularly deep learning). Expertise in statistical learning and random processes, Docker, DBMS (e.g. MySQL, Redis), and Google Cloud Services (GCP) is a plus. The candidate must have a track-record of publications/scientific writing and have strong proficiency in all four skills of English language, including ideally experience in writing scientific manuscripts.  

Ph.D. in Computer Science, Electrical Engineering, or a related field with a strong emphasis on AI, machine learning, or related fields. Candidates for the training or those with without advances degrees who have prior work experience are also encouraged to apply. Surgical trainees with relevant prior experiences who are able to take time out of their training (lab years) are also encouraged to apply. 

The application is open to both clinicians, research candidates, and those in technology sector including those currently in training or have recently completed training (post-doc). The expectation at the end of the fellowship is that the fellow will be well prepared to become a leader in Healthcare AI/ML, either in the academic or biotechnology setting. 

The ideal candidate must have strong expertise in data structures and algorithms, Python programming language (including libraries such as Pandas, Scikit-learn), shell scripting, Tensorflow/PyTroch (preferred), and/or machine learning (particularly deep learning). Expertise in statistical learning and random processes, Docker, DBMS (e.g. MySQL, Redis), and Google Cloud Services (GCP) is a plus. The candidate must have a track-record of publications/scientific writing and have strong proficiency in all four skills of English language, including ideally experience in writing scientific manuscripts.