STEM OPT Postdoctoral Research Fellow Jobs
Postdoctoral Research Fellow roles at universities and research institutions are among the strongest fits for STEM OPT students. Your 24-month STEM OPT extension covers the full arc of a standard postdoc appointment, and most academic employers are already enrolled in E-Verify. Your STEM degree field must align with the CIP code on your I-20.
Find STEM OPT Postdoctoral Research Fellow JobsOverview
Showing 5 of 205+ Postdoctoral Research Fellow jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 205+ Postdoctoral Research Fellow Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Postdoctoral Research Fellow roles.
Get Access To All JobsJob Ref:
JR-4397
Location:
450 Brookline Ave, BOSTON, MA 02215
Category:
Fellowships
Employment Type:
Full time
Work Location:
Onsite: occasional remote
Salary/Pay Rate:
$72,000.00 - $76,385.00 per year
Overview
The Jeselsohn Lab and the Breast Oncology Center Computational Biology (BCCB) group is looking for a highly motivated and talented postdoctoral researcher with a computational or bioinformatic background to join the Department of Breast Oncology at Dana-Farber Cancer Institute. The candidate for this position will join a team of computational biologists to work on multi-omic sequencing datasets (DNA, RNA, epigenetic, spatial transcriptomics and spatial proteomics) in the context of pre-clinical and multiple clinically oriented studies in order to help advance efforts for translational cancer genomics and precision cancer medicine. The candidate will report to the BCCB Director Dr. Rinath Jeselsohn and the BCCB leadership (Dr. Gomez Tejeda Zanudo, Dr. Daniel Abravanel). Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
The Breast Oncology Center Computational Biology group leads the computational biology efforts to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done by using existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain treatment and diagnostic information. The aim of these efforts is to identify genomic alterations and transcriptional changes associated with tumor evolutionary dynamics, mechanisms of resistance, and therapeutic benefit. These datasets and multi-omics associations could help identify novel approaches for personalized care in oncology. These datasets and associations may provide support for new methods in clinical decision-making, tumor markers for rational drug development, and new insights into tumor biology through innovative analyses. In addition, the Jeselsohn lab utilizes pre-clinical model systems and high-throughput methodologies to investigate mechanisms of drug resistance and novel therapeutic targets in breast cancer.
Responsibilities
- Drive scientific projects by analyzing and interpreting large-scale and multidimensional omics datasets and clinical outcomes to advance translational science with immediate potential clinical application.
- Develop and implement AI and machine learning methodologies for integrative analysis of cancer genomic data, including its implementation into software tools that will be widely distributed and shared with the scientific community.
- Participate in the design and implementation of algorithms to analyze and integrate large data as well as the maintenance of datasets and shared tools.
- Lead and contribute to manuscript preparation, scholarly reports and presents at scientific conferences, as well as internal and external project-team reports.
- Actively participate in project team and group meetings.
- Participate within a team of scientists to foster a culture of scientific excellence.
- Assist in the mentorship of junior analytical staff members and graduate students.
QUALIFICATIONS
- A PhD in computational biology, bioinformatics, statistics, computer science (Machine Learning), physics, math, engineering or a related quantitative discipline is required.
- Experience with cancer genomics, computational analysis, algorithm development, statistics and machine learning.
- Experience with AI and machine learning methods applied to cancer genomics.
- Proficiency in at least one modern programming language. Experience with a scientific programming environment, such as python or R, is preferred.
- Strong communication skills.
- Excellent oral, written, interpersonal, and organizational skills and the ability to perform both self-directed and guided research are crucial.
- Demonstrated ability to work as part of a large, interdisciplinary team. Ability to meet deadlines and multitask efficiently is a must.
At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.
Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.
EEO Poster
Pay Transparency Statement
The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications.
For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).
$72,000.00 - $76,385.00
Job Ref:
JR-4397
Location:
450 Brookline Ave, BOSTON, MA 02215
Category:
Fellowships
Employment Type:
Full time
Work Location:
Onsite: occasional remote
Salary/Pay Rate:
$72,000.00 - $76,385.00 per year
Overview
The Jeselsohn Lab and the Breast Oncology Center Computational Biology (BCCB) group is looking for a highly motivated and talented postdoctoral researcher with a computational or bioinformatic background to join the Department of Breast Oncology at Dana-Farber Cancer Institute. The candidate for this position will join a team of computational biologists to work on multi-omic sequencing datasets (DNA, RNA, epigenetic, spatial transcriptomics and spatial proteomics) in the context of pre-clinical and multiple clinically oriented studies in order to help advance efforts for translational cancer genomics and precision cancer medicine. The candidate will report to the BCCB Director Dr. Rinath Jeselsohn and the BCCB leadership (Dr. Gomez Tejeda Zanudo, Dr. Daniel Abravanel). Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
The Breast Oncology Center Computational Biology group leads the computational biology efforts to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done by using existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain treatment and diagnostic information. The aim of these efforts is to identify genomic alterations and transcriptional changes associated with tumor evolutionary dynamics, mechanisms of resistance, and therapeutic benefit. These datasets and multi-omics associations could help identify novel approaches for personalized care in oncology. These datasets and associations may provide support for new methods in clinical decision-making, tumor markers for rational drug development, and new insights into tumor biology through innovative analyses. In addition, the Jeselsohn lab utilizes pre-clinical model systems and high-throughput methodologies to investigate mechanisms of drug resistance and novel therapeutic targets in breast cancer.
Responsibilities
- Drive scientific projects by analyzing and interpreting large-scale and multidimensional omics datasets and clinical outcomes to advance translational science with immediate potential clinical application.
- Develop and implement AI and machine learning methodologies for integrative analysis of cancer genomic data, including its implementation into software tools that will be widely distributed and shared with the scientific community.
- Participate in the design and implementation of algorithms to analyze and integrate large data as well as the maintenance of datasets and shared tools.
- Lead and contribute to manuscript preparation, scholarly reports and presents at scientific conferences, as well as internal and external project-team reports.
- Actively participate in project team and group meetings.
- Participate within a team of scientists to foster a culture of scientific excellence.
- Assist in the mentorship of junior analytical staff members and graduate students.
QUALIFICATIONS
- A PhD in computational biology, bioinformatics, statistics, computer science (Machine Learning), physics, math, engineering or a related quantitative discipline is required.
- Experience with cancer genomics, computational analysis, algorithm development, statistics and machine learning.
- Experience with AI and machine learning methods applied to cancer genomics.
- Proficiency in at least one modern programming language. Experience with a scientific programming environment, such as python or R, is preferred.
- Strong communication skills.
- Excellent oral, written, interpersonal, and organizational skills and the ability to perform both self-directed and guided research are crucial.
- Demonstrated ability to work as part of a large, interdisciplinary team. Ability to meet deadlines and multitask efficiently is a must.
At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.
Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.
EEO Poster
Pay Transparency Statement
The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications.
For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).
$72,000.00 - $76,385.00
See all 205+ STEM OPT Postdoctoral Research Fellow Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Postdoctoral Research Fellow Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization in Postdoctoral Research Fellow
Verify your CIP code before applying
Your STEM OPT extension depends on the Classification of Instructional Programs code tied to your degree, not just your major title. Cross-check your I-20's CIP code against USCIS's list of STEM-designated programs before targeting postdoc openings in a specific field.
Confirm E-Verify enrollment before accepting offers
Universities and national labs almost always participate in E-Verify, but private research institutes sometimes don't. Search the E-Verify employer search tool by institution name to confirm enrollment before your DSO submits your STEM OPT extension application.
Build your I-983 training plan around research deliverables
Your I-983 must name specific learning objectives tied to your STEM degree field. For postdocs, map each objective to a defined research milestone, such as a published paper or lab method, so your training plan survives a SEVIS audit.
Target labs with recurring postdoc pipelines
PIs who have supervised postdocs before understand the E-Verify and I-983 requirements and won't be surprised by them. Search DOL LCA disclosure data by job title and institution to find labs with a consistent pattern of sponsoring postdoctoral roles on work authorization.
Search Migrate Mate to find E-Verify enrolled research employers
Postdoc openings at non-E-Verify employers disqualify you for STEM OPT before an offer is even made. Migrate Mate filters postdoctoral positions to show only employers enrolled in E-Verify, so you don't waste applications on institutions that can't authorize your extension.
Start your extension application 90 days before OPT ends
USCIS requires your STEM OPT extension application to be filed before your initial OPT EAD expires. A timely filing triggers a 180-day cap-gap that keeps you authorized while USCIS adjudicates, but the clock starts only if you file on time.
Frequently Asked Questions
Does a Postdoctoral Research Fellow role qualify for the STEM OPT extension?
Yes, if your degree field matches the CIP code on your I-20 and the postdoc involves work directly related to that field. Most postdoc appointments at universities and research institutions satisfy the STEM OPT requirement because the research directly applies knowledge from your STEM degree. Your DSO confirms eligibility when recommending the extension in SEVIS.
Does my postdoctoral employer need to be enrolled in E-Verify?
Yes. E-Verify enrollment is a hard requirement for STEM OPT employers. Without it, your employer can't legally employ you on the extension regardless of the role's research content. Most universities and federal research labs are already enrolled, but confirm enrollment through the E-Verify employer search before accepting any offer, not after.
What goes into the I-983 training plan for a postdoc position?
The I-983 must list specific learning objectives tied to your STEM degree field, the supervision structure, and how the employer will evaluate your progress. For postdocs, frame each objective around a concrete research deliverable, such as completing a set of experiments or co-authoring a publication, and have your PI sign off before your DSO submits the recommendation.
What happens to my STEM OPT authorization if my postdoc appointment ends early?
You have a 60-day grace period after your employment ends to find a new qualifying employer, change status, or depart the U.S. If you start a new postdoc, your new employer must also be enrolled in E-Verify and a new or amended I-983 is required. Your DSO must be notified within five business days of any material change in your training plan.
How do I find Postdoctoral Research Fellow openings at E-Verify enrolled employers?
Migrate Mate filters postdoc listings to show only employers enrolled in E-Verify, which is the threshold requirement for STEM OPT eligibility. You can also cross-reference DOL LCA disclosure data to see which research institutions have a track record of hiring on work authorization for postdoctoral job titles before you invest time in an application.