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Data Science Postdoc Jobs in Boston, MA (NOW HIRING)

Dyne Therapeutics

Scientist, RNA Chemistry

Waltham, MA · On-site

Interpretation of analytical data (HPLC, LCMS)to enableimprovedpurity and yields of synthesized ... Postdoctoral experience is a plus * Hands-on experience operating oligonucleotide synthesis and ...

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How much do data science postdoc jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for data science postdoc in Boston, MA is $61.72, according to ZipRecruiter salary data. Most workers in this role earn between $50.67 and $73.12 per hour, depending on experience, location, and employer.

What are typical daily or weekly responsibilities for a Data Science Postdoc?

Data Science Postdocs often spend their days designing and conducting advanced data analyses, developing and testing predictive models, and communicating results through reports or academic publications. They frequently collaborate with faculty, graduate students, and industry partners on interdisciplinary projects, contributing their quantitative expertise. Additionally, Data Science Postdocs may mentor junior researchers, participate in lab meetings, present findings in seminars, and contribute to grant proposals. This dynamic environment provides opportunities to deepen research skills, publish impactful work, and prepare for future career advancement in academia or industry.

What are the key skills and qualifications needed to thrive in the Data Science Postdoc position, and why are they important?

To thrive as a Data Science Postdoc, you need advanced analytical skills, expertise in statistical modeling, a doctoral degree in a quantitative field, and proven experience with data-driven research. Proficiency in programming languages like Python or R, along with experience using machine learning libraries, data visualization tools, and version control systems, is typically required. Excellent problem-solving abilities, collaborative teamwork, and effective communication skills help set outstanding candidates apart. These attributes are crucial for advancing knowledge, publishing impactful research, and working effectively within interdisciplinary research teams.

What is a Data Science Postdoc job?

A Data Science Postdoc is a temporary research position, typically at a university or research institution, for individuals who have recently completed a PhD. The role focuses on applying advanced data science techniques, such as machine learning, statistical modeling, and big data analysis, to solve complex research problems. Postdocs often work on interdisciplinary projects, collaborate with faculty, publish academic papers, and may also contribute to teaching. The goal is to build expertise, advance knowledge in a specific domain, and prepare for roles in academia, industry, or government.

What are popular job titles related to Data Science Postdoc jobs in Boston, MA? For Data Science Postdoc jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Science Postdoc jobs in Boston, MA look for? The top searched job categories for Data Science Postdoc jobs in Boston, MA are:
Data Science Postdoc jobs near you
Postdoctoral Associate, Neurology, Boston University Chobanian & Avedisian School of Medicine

Postdoctoral Associate, Neurology, Boston University Chobanian & Avedisian School of Medicine

Boston University

Boston, MA • On-site

$70K/yr

Full-time

Posted 23 days ago

Boston University rating

7.9

Company rating: 7.9 out of 10

Based on 51 frontline employees who took The Breakroom Quiz

181st of 541 rated colleges and universities

Job description


Location: Boston University School of Medicine (Boston, MA)
Supervisors: Jesse Mez, MD, MS; Jon Cherry, PhD; Vijay K. Kolachalama, PhD
Position summary
We seek a motivated postdoctoral research fellow to join an interdisciplinary team investigating post traumatic neurodegeneration using digital neuropathology whole slide images (WSIs), clinical phenotypes, and machine learning. The fellow will play a central "bridge" role between neuropathology, clinical neurology, and data science, working across brain bank cohorts (UNITE, Framingham Heart Study, and the BU ADRC) to develop and validate computational classifiers and to link image derived pathology features with lifetime clinical data. The position is ideal for a candidate with a strong neuroscience background-particularly in head trauma and/or neurodegenerative disease-who wants to combine wet lab neuropathologic techniques with computational model development and translational analyses.
Project overview
This NIH funded project leverages WSIs and richly phenotyped cohorts to: develop algorithms to detect neuropathologic signatures of chronic traumatic encephalopathy (CTE); identify neuropathologic features associated with repetitive head impact (RHI) exposure; and map pathology patterns to clinical outcomes observed in life (cognitive impairment, behavioral dysregulation, parkinsonism, etc.). The fellow will help build and curate image datasets, generate and validate annotations and experimental labels, design and apply machine learning/image analysis pipelines, and integrate pathology features with clinical and epidemiologic data across cohorts to address these aims.
Key responsibilities
  • Lead development, evaluation, and refinement of machine learning and image analysis pipelines for WSIs, including preprocessing, annotation workflows, model training/validation, and interpretability analyses.
  • Curate and harmonize WSI datasets and associated metadata from multiple brain banks; contribute to quality control
  • Design and perform targeted wet lab neuropathologic experiments (e.g., immunohistochemistry, staining optimization, region specific sampling) to validate computational findings and generate ground truth labels as needed.
  • Integrate pathology derived quantitative features with clinical and cohort data to test associations with RHI exposure and clinical phenotypes; collaborate on statistical analyses.
  • Collaborate closely with neuropathologists, clinicians, and computational scientists to interpret findings in a neuropathologic and clinical context, and iteratively improve models.
  • Maintain reproducible, well documented workflows (code, pipelines, notebooks) and manage data in accordance with BU policies and grant requirements.
  • Disseminate results through manuscripts, grant reports, and presentations; assist with mentoring trainees and coordinating with collaborators.

Application instructions
Please submit a single PDF to Dr. Jesse Mez at jessemez@bu.edu containing:
  1. Cover letter describing your interest and relevant experience across neuropathology, neurology, and data science, and how you envision bridging wet lab and computational work.
  2. Curriculum vitae (with publication list).
  3. Contact information for three references (one should be your PhD/postdoc advisor or equivalent).
  4. Representative papers, or other relevant work samples.

Review of applications will begin immediately and continue until the position is filled.
Required Skills
Qualifications
Required
  • PhD, MD/PhD, or equivalent doctoral degree in neuroscience, neuropathology, computational biology, biomedical engineering, computer science with neuroscience focus, or closely related field.
  • Demonstrated neuroscience background with interest in head trauma and/or neurodegenerative disease.
  • Experience in at least one of the following: neuropathologic methods (histology/IHC), digital pathology/WSI workflows, or machine learning for biomedical images.
  • Strong written and oral communication skills and proven ability to work effectively in interdisciplinary teams.
  • Track record of scholarly productivity (publications, preprints, or substantial project deliverables).

Preferred
  • Programming proficiency in Python and/or R; experience with deep learning frameworks (PyTorch, TensorFlow) preferred.
  • Prior experience working with whole slide image formats, slide scanners, annotation tools (HALO, QuPath, ASAP, SlideRunner, etc.), and image pre processing.
  • Experience integrating multi modal datasets (pathology images, clinical, epidemiologic cohorts).
  • Familiarity with neuropathologic features and proteinopathies (tau, TDP 43, amyloid, alpha synuclein).
  • Hands on wet lab histology or IHC experience.
  • Prior involvement with brain bank data or large longitudinal cohort studies.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, natural or protective hairstyle, religion, sex, age, national origin, physical or mental disability, sexual orientation, gender identity, genetic information, military service, pregnancy or pregnancy-related condition, or because of marital, parental, or veteran status. We are a VEVRAA Federal Contractor.

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About Boston University

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Boston University is an international, comprehensive, private research university, committed to educating students to be reflective, resourceful individuals ready to live, adapt, and lead in an interconnected world. Boston University is committed to generating new knowledge to benefit society. We remain dedicated to our founding principles: that higher education should be accessible to all and that research, scholarship, artistic creation, and professional practice should be conducted in the service of the wider community—local and international. These principles endure in the University’s insistence on the value of diversity, in its tradition and standards of excellence, and in its dynamic engagement with the City of Boston and the world. Boston University comprises a remarkable range of undergraduate, graduate, and professional programs built on a strong foundation of the liberal arts and sciences. With the support and oversight of the Board of Trustees, the University, through our faculty, continually innovates in education and research to ensure that we meet the needs of students and an ever-changing world.

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Year founded

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