Bioinformaticist I

Our laboratory studies breast and ovarian cancer, striving to discover the mechanisms behind disease initiation, progression and drug resistance. We are seeking a highly motivated Bioinformaticist with knowledge in computational image analysis and proficiency in Python. In this position, you will be supervised by our image analysis expert and will work together with members of the lab who are performing cyclic immunofluorescence (CyCIF) experiments. These experiments aim to better understand the earliest changes in the initiation of tumorigenesis as well as the heterogeneity of cell states and their spatial distribution within a tumor. CyCIF is applied to tissues from a diverse set of sources, including genetically engineered mice, patient-derived xenografts propagated in mice, tumor cell line xenografts, and patient samples. As a Bioinformaticist, your primary responsibility will be analyzing fluorescent imaging data to quantify the levels of protein expression in individual cells and ‘cell neighborhoods’. This will involve identifying the appropriate single cell segmentation approaches for each tissue type and apply them iteratively to acquire fluorescence signal intensities that can be used to perform spatial analyses. You will interpret initial results and carry out follow-up analyses, developing the necessary approaches and writing code for their execution, and training other RAs on the project in using developed code for new approaches for segmentation and analysis. You will communicate findings to the lead investigator of each project and, through collaborative discussions, determine which additional analyses need to be performed. This position provides an opportunity to make significant contributions to many projects in our lab.

Technical Duties and Responsibilities

• Carry out image processing from tissue or tumor sections by registering and stitching images acquired on a Rarecyte microscope using a Python-based script as well as other approaches as they are developed. 
• Perform fluorescent image processing, quality control, and cell segmentation using multiple approaches: identify appropriate single cell segmentation approaches for each tissue type and apply them iteratively, checking accuracy to obtain single cell data.
• Design, develop and test computational methods and displays to identify correlations between proteins expressed in single cells, to identify changes in protein expression in cells from tissues of women at high risk for cancer, and to identify differences in tumor responses to cancer therapies. 
• Using biological knowledge, identify candidate cell neighborhoods to define using cellular protein expression, then implement appropriate computational approaches to define these neighborhoods (e.g., Latent-Dirichlet Algorithm, network analysis, etc.).
• Work with scRNASeq and spatial transcriptomics datasets, including probing gene signature expression and comparing expression between groups using correct statistical models (e.g., Linear Mixed Model, Bayesian). 
• Interpret initial results and carry out follow-up analyses, developing the necessary approaches and writing code for their execution; work with biologists on data analysis and with other bioinformaticists on the team to strategize computational approaches to execute follow-up analyses. 
• Communicate findings with project collaborators, and prepare figures and materials for presentations as needed.
• Lead and train biologists and RAs on computational tools developed for segmentation and analysis. 

Basic Qualifications:

• Bachelor’s degree in Biological Sciences or other related field required.
• 3+ years’ experience in the area of bioinformatics. 

Additional Qualifications and Skills:

• Master's in Bioinformatics, Biological Engineering, Computer Science or related field STRONGLY PREFERRED. 
• Familiarity with computational image analysis STRONGLY PREFERRED. 
• Proficient in Python and R (3 years coding experience, including academic coursework).
• Experience with single cell analysis, statistics, data presentation and documentation.
• Experience working on collaborative programming projects through platforms like Github.
• Ability to make sound judgements and to problem solve.
• Willingness to learn and introduce new approaches to image analysis as required for individual projects.

• Appointment End Date: This is a one-year term position from the date of hire, with the possibility of extension, contingent upon work performance and continued funding to support the position. 
• Standard Hours/Schedule: 35 hours per week
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.
• Pre-Employment Screening: Identity, Education
• Other Information: Please note that we are currently conducting a majority of interviews and onboarding remotely and virtually. We appreciate your understanding.
• Staying Informed About Your Application: Due to the high volume of applications, we may not always be able to reach out right away, but you can track your status anytime through the Careers@Harvard portal.

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Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 056. Please visit  Harvard's Salary Ranges to view the corresponding salary range and related information. 

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to: 

• Generous paid time off including parental leave 
• Medical, dental, and vision health insurance coverage starting on day one 
• Retirement plans with university contributions 
• Wellbeing and mental health resources 
• Support for families and caregivers 
• Professional development opportunities including tuition assistance and reimbursement 
• Commuter benefits, discounts and campus perks 

Learn more about these and additional benefits on our Benefits & Wellbeing Page. 

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.