Principal Research Scientist I

Key Skills

Aartificial intelligence, AWS, C++, Data Analysis, Deep Learning, Keras software library, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, Statistics, TensorFlow

Job Description

AbbVie Precision Medicine Pathology is committed to driving tissue based translational and biomarker efforts for our pre-clinical and clinical stage programs. We are seeking a highly motivated scientist with expertise in digital pathology, including image acquisition and analysis using cutting edge deep learning technology. Candidates for this senior position should have several years of experience in the field, a passion for research, and a track record of productivity and accomplishments. They should enjoy working in a fast-paced, dynamic and highly interactive environment. Their scientific leadership will enable them to independently and expertly guide teams in their approaches to quantitative image derived data generation and interpretation.

As an imaging scientist you will be embedded in a small team that works closely with colleagues in the various pathology laboratories as well as with the research pathologists. You will provide scientific leadership to our team as you interface with investigators in discovery and late-stage research across our spectrum of disease areas which ranges from oncology, cancer immunotherapy, immunology, to neuroscience.

This position is based on our South San Francisco campus.

Title is flexible and will be commensurate to qualifications and experience.

Key responsibilities

• Design, and, in collaboration with colleagues within the Pathology group, advance cutting-edge research and development in Artificial Intelligence for Digital Pathology by developing AI digital pathology solutions
• Support the logistics and maintenance of in-house digital pathology platforms; provide leadership for the recommendation, adoption and implementation of new technologies
• Execute approaches for acquisition, analysis, interpretation and presentation of tissue derived image data to inform research projects and teams.
• Contribute to or lead efforts for comprehensive computational data analysis within the digital pathology space and beyond as necessary for integration of data flows from a variety of platforms, sources or technologies.
• Articulate hypotheses, work plans, and present results to a variety of audiences in both oral and written communications
• Identify, implement and utilize cutting edge technology for the analysis of images or similar data derived from a variety of imaging modalities and platforms including bright field, darkfield multicolor fluorescent or mass spectrometry
• Conceive and guide external collaborations and projects in the digital pathology space
• Provide training and guidance for the use of established methodology, troubleshooting of assays, and in the development or deployment of novel techniques

Minimum Qualifications

• PhD, MS or BS in computer science, electrical engineering, biomedical engineering, bioinformatics, computational biology, physics, mathematics or equivalent.

• Demonstrated programming experience (python/MATLAB/C++) and machine learning and deep learning frameworks (e.g. TensorFlow, Keras, PyTorch)

• Hands-on experience developing deep learning models for various computer vision tasks (e.g. object detection, segmentation, classification)

• Demonstrated desire and ability to learn, understand and master new techniques or technologies
• Strong scientific writing and strong verbal communication skills
• Ability to thrive in a fast paced, multi-disciplinary, matrixed environment.
• Ability to work effectively on multiple projects and strong passion to use cutting edge technology for drug discovery

Preferred Qualifications

• MS or PhD in a relavant field with 5+ years of experience building AI models on real world data.

• Experience building deep learning models with emphasis on representation learning approaches such as few-shot, zero-shot learning, self-supervised learning, transfer learning, multi-modal learning and more.

• Experience writing code and developing software in an industry setting. Experience developing software on Linux OS.

• Familiarity with cloud compute (e.g. AWS) and high performance compute platform.

• Familiarity with concepts of cell and molecular biology applicable to immunology, cancer immunotherapy, oncology or neuroscience

• Experience of working with digital histopathology and microscopy images – bright field and dark field or with high resolution/large images and file formats.

• Nice to have experience using digital pathology tools such as Halo and VisioPharm

• Experience with statistics, data analysis and visualization of multi-dimensional data.

Benefits and Amenities

• Access to and close interaction with a small team of experts

• Access to state-of-the-art facilities and on-site amenities

• Competitive pay

Equal Employment Opportunity

At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.

AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.