AbbVie Postdoc - Postdoctoral Fellow: Pathology/Deep Learning/Bioinformatics in Worcester, Massachusetts

Description:

AbbVie is a global, research-based biopharmaceutical company formed in 2013 following separation from Abbott Laboratories. The company's mission is to use its expertise, dedicated people and unique approach to innovation to develop and market advanced therapies that address some of the world's most complex and serious diseases. Together with its wholly-owned subsidiary, Pharmacyclics, AbbVie employs more than 28,000 people worldwide and markets medicines in more than 170 countries.

At AbbVie, our vision is to be recognized as a biopharmaceutical company delivering a consistent stream of innovative medicines that solve serious health issues and have a remarkable impact on people’s lives.

To be successful, we need outstanding individuals willing to challenge themselves to find the best solutions for our patients. The AbbVie Postdoc program is one way we are doing just that.

Through our Postdoc program, we are hiring postdocs from key academic institutions for preferred areas of science in the U.S., while providing a unique opportunity for participants to build a solid career foundation in the pharmaceutical industry while building the AbbVie brand as an employer of choice for scientific talent.

The program offers a balance of structured learning and work experience, with accessibility to high-level knowledge building across the drug development continuum to help participants understand how everything fits together and is put into practice. It also provides them with a chance to establish working relationships with some of the world’s most respected scientists and leaders in the industry.

Participants in the Postdoc program play an integral part in our continued success and will help us to further grow as a leader in our industry.

The Immunology Pharmacology groupis focused on improving our understanding of the pathology of inflammatory bowel disease and how therapies work to produce mucosal healing and ultimately, remission. The objective of this fellowship is to use conventional and emerging deep learning methods to develop a reproducible method to assess mucosal healing in histologic sections from ulcerative colitis (UC) endoscopic biopsies based on Geboes classification. This postdoctoral position of 3 years will be based in Worcester, MA at the AbbVie Bioresearch Center.

There are three major aims to this project:

Aim 1: Define the simplest and best image analysis methods to assess morphologic endpoints recognized in the Geboes classification in UC and develop classifiers using conventional image analysis methods on a set of well-annotated samples from UC subjects and normal samples;

Aim 2 : Apply deep learning by iterative training to those features that cannot be defined by conventional methods on this same test set.

Aim 3: Apply quantitative methods developed in Aim 1 and Aim 2 to a blinded cohort of 50 slides with comparison to Geboes scores, endoscopy scores and clinical outcome.

The application of image analysis and deep learning to histopathology is a rapidly expanding field of bioinformatics that is largely applied to oncologic and neuropathology. The successful application of methods established for cancer and neurology to UC would be transformative. For the post doc, this would result in a major publication on a subject about which little is written, for Abbvie this would help to better predict response to therapy, for patients, this would result in a method better than endoscopy to define whether their therapy is working.

Key responsibilities:

· Work with a team of pathologists, bioinformaticians and statisticians to design and execute best “fit for purpose” algorithms that can be applied to ulcerative colitis.

· Apply these algorithms to training and test sets to determine their correlation to existing histologic methods.

· Work to expand understanding of the cost:benefit of using deep learning methods compared to conventional (commercially available) image analysis methods

Qualifications:

Qualifications:

· Successful completion and defense of a Ph.D in a background in bioinformatics, artificial intelligence, pathology informatics, or biomedical engineering

· Demonstrated skills in computer vision, machine learning/deep learning

· Proficient in one or more languages and platforms: Java, Python, C , C, JavaScript, MATLAB, R, GoogleNet, Caffe.

· Familiarity with digital pathology, conventional image analysis software (Visiopharm/Definiens), and anatomic pathology is desired

Application requirements:

· Curriculum Vitae

· A narrative on why your academic training qualifies you for this position and why you have an interest in this position.

· Three letters of recommendation, preferably one from your PI and at least one from a member of your thesis committee.

· Must be authorized to work in the U.S.

Key AbbVie Competencies:

· Builds strong relationships within and outside a team to enable higher performance.

· Learns fast and grasps the “essence” of a result, and can change course quickly when indicated.

· Raises the bar and is never satisfied with the status quo.

· Creates a learning environment, open to suggestions and experimentation for improvement.

· Embraces the ideas of others, nurtures innovation and manages innovation to reality.

https://abbvie.taleo.net/careersection/2/jobsearch.ftl?keyword=postdoctoral fellow

For further information on the company and its people, portfolio and commitments, please visit www.abbvie.com . Follow @abbvie on Twitter or view careers on our Facebook or LinkedIn page.

Equal Opportunity Employer Minorities/Women/Veterans/Disabled

Job Classification: Experienced
Job: RESEARCH AND DEVELOPMENT
Primary Location: USA-Massachusetts-Worcester
Organization: Headquarters
Schedule: Full-time
Shift: Day
Travel: No
Req ID: 1703104

Equal Opportunity Employer Minorities/Women/Veterans/Disabled