8,690 Research Fellowship jobs in the United States

Frances E. Malamy had deep roots within PEM and the Phillips Library. A long-standing member of the museum family, she dedicated tireless hours processing manuscripts. She was a unique and extraordinary individual who firmly believed that the Phillips Library provides value to the academic community and the public, and realized the importance of the collection and its outreach impact on the greater intellectual world. To sustain the contributions that Frances made to the library, her husband Michael and her two children, Jocelyn and Adam, have funded this fellowship as a lasting tribute to her memory and her interest in the Phillips Library and the world of scholarship.

The Frances E. Malamy Research Fellowship is awarded to one recipient each year to perform independent scholarly research. Fellowships awarded may be taken in the calendar year following an accepted application. The recipient receives a $5,500 award, payable in two equal installments, at the middle and conclusion of their residency.

Qualification to be eligible for the fellowship are listed below:

• Research must be centered in the library's archives and manuscripts collections.
• The fellowship requires in-library research for a minimum of eight weeks, not to be divided into more than two terms.
• The program culminates in the submission of a research summary for the benefit of the library's audiences, typically a public lecture or discussion, but the format of this is negotiable. PEM reserves the right to publicize the resulting product in order to promote research within the collection.
• This fellowship is available to U.S. citizens, green card holders and holders of an F1 student visa or a J1 practicum/training visa.

To be considered for this fellowship, please have your application submitted by Sunday, October 26, 2025.

PEM strives to create a community of belonging that draws upon the widest pool of talent, embracing individuals of all backgrounds, life experiences, and perspectives. We seek candidates who can contribute to helping us achieve our goals and encourage you to apply for our open positions identifying the contributions you can make.

PEM considers all qualified candidates without regard to race, color, religion, sex, age, national origin, disability status, protected veteran status, gender identity, sexual orientation, genetic information, pregnancy or pregnancy related condition or any other characteristic protected by law.

• Assist in gathering and organizing research data from various sources.
• Perform data cleaning and preprocessing to ensure accuracy and consistency.
• Conduct exploratory data analysis to identify trends, patterns, and anomalies.
• Support the development and implementation of statistical models.
• Create clear and informative data visualizations and reports using various tools.
• Collaborate with team members on research projects and data interpretation.
• Assist in literature reviews and summary of relevant research papers.
• Maintain organized documentation of data sources, methodologies, and findings.
• Learn and apply new analytical techniques and software.
• Contribute to the preparation of research findings for presentations and publications.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Foundational knowledge of statistical concepts and data analysis techniques.
• Familiarity with data analysis tools such as Python (Pandas, NumPy), R, or SQL is a plus.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) is beneficial.
• Strong analytical and problem-solving skills.
• Excellent attention to detail and commitment to data accuracy.
• Good written and verbal communication skills.
• Ability to work independently and as part of a remote team.
• Enthusiasm for research and data-driven discovery.

• Assist senior researchers in designing, developing, and implementing machine learning models.
• Collect, clean, and preprocess large datasets for training and evaluation purposes.
• Perform exploratory data analysis to identify patterns and insights.
• Implement and test algorithms for various AI applications, including natural language processing, computer vision, or reinforcement learning.
• Contribute to the documentation of research findings, methodologies, and code.
• Collaborate with team members through virtual meetings and shared code repositories.
• Stay updated on the latest research papers and advancements in the field of artificial intelligence and machine learning.
• Participate in research discussions and present preliminary findings to the team.
• Support the development of prototypes and proof-of-concepts.
• Engage in learning new tools and techniques relevant to AI research.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• Solid understanding of fundamental machine learning concepts and algorithms.
• Proficiency in Python and relevant libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas.
• Experience with data manipulation and analysis techniques.
• Familiarity with version control systems like Git.
• Strong problem-solving abilities and a logical, analytical mindset.
• Excellent communication skills, with the ability to articulate technical concepts clearly in a remote setting.
• Self-motivated and able to work independently with minimal supervision.
• Enthusiasm for artificial intelligence and a strong desire to learn and contribute.
• Access to a reliable internet connection and a suitable remote work environment.

• Design and perform advanced bioinformatics analyses on large-scale biological datasets (genomic, transcriptomic, proteomic, etc.).
• Develop, implement, and validate novel computational algorithms and pipelines.
• Interpret complex data to identify patterns, biomarkers, and scientific insights.
• Collaborate with experimental biologists, clinicians, and other researchers to design studies and analyze results.
• Contribute to grant proposals and manuscript preparation for publication in peer-reviewed journals.
• Stay abreast of the latest advancements in bioinformatics, computational biology, and related fields.
• Develop and maintain robust code and documentation for bioinformatics tools and analyses.
• Present research findings at scientific meetings and conferences.
• Mentor junior scientists and research staff in bioinformatics techniques.

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
• Minimum of 7 years of post-doctoral or industry experience in bioinformatics research.
• Demonstrated expertise in analyzing large-scale biological datasets, including next-generation sequencing data.
• Proficiency in programming languages such as Python, R, or Perl, and experience with bioinformatics libraries.
• Strong understanding of statistical methods and machine learning techniques applicable to biological data.
• Experience with bioinformatics databases, tools, and reference genomes.
• Familiarity with cloud computing environments (e.g., AWS, Google Cloud) and big data technologies is a plus.
• Excellent problem-solving, analytical, and communication skills.
• Proven ability to conduct independent research and work effectively in a remote team.

• Design, implement, and manage complex research projects in molecular biology, focusing on disease mechanisms and therapeutic development.
• Lead and mentor a team of research associates and post-doctoral fellows, fostering a collaborative and productive research environment.
• Develop and optimize novel molecular biology assays and experimental protocols.
• Perform rigorous data analysis, interpretation, and presentation of research findings.
• Author and co-author scientific publications for peer-reviewed journals and present research at national and international conferences.
• Contribute to the writing and submission of grant proposals to secure research funding.
• Manage laboratory resources, including equipment, consumables, and budgets.
• Collaborate with internal and external stakeholders, including clinical teams and industry partners.
• Ensure compliance with all laboratory safety regulations and ethical guidelines.
• Stay abreast of the latest advancements and emerging technologies in molecular biology and related fields.

• Ph.D. in Molecular Biology, Genetics, Biochemistry, or a related life sciences discipline.
• A minimum of 7 years of postdoctoral and/or research experience, with a strong emphasis on independent research and project leadership.
• Demonstrated track record of significant scientific contributions, evidenced by a strong publication record in reputable journals.
• Extensive hands-on experience with a wide range of molecular biology techniques (e.g., PCR, qPCR, Western blotting, CRISPR, next-generation sequencing, cell culture).
• Proven experience in experimental design, data analysis (including statistical methods), and interpretation.
• Excellent leadership, communication, and interpersonal skills, with the ability to mentor and inspire a research team.
• Experience in grant writing and securing research funding is highly desirable.
• Proficiency in scientific software and databases.

• Lead the design, development, and implementation of advanced statistical models and machine learning algorithms to analyze large, complex datasets from scientific experiments.
• Extract, clean, and transform data from diverse sources, ensuring data integrity and accuracy for analysis.
• Develop predictive models and analytical solutions to address challenging scientific questions and accelerate research breakthroughs.
• Collaborate closely with research scientists, engineers, and domain experts to understand their data needs and translate them into analytical frameworks.
• Communicate complex findings and insights clearly and effectively to both technical and non-technical stakeholders through reports, presentations, and visualizations.
• Mentor junior data scientists and contribute to the growth and development of the data science team.
• Stay current with the latest advancements in data science, machine learning, and relevant scientific fields, and evaluate their applicability to our research initiatives.
• Design and conduct A/B tests and other experimental designs to validate hypotheses and measure the impact of interventions.
• Develop and maintain data pipelines and workflows to ensure efficient data processing and analysis.
• Contribute to the strategic vision for data utilization and analytics within the organization.

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Physics, Biology, or a related quantitative field.
• 10+ years of professional experience in data science, with a significant focus on scientific research or R&D environments.
• Expertise in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
• Deep understanding of statistical modeling, machine learning techniques (e.g., regression, classification, clustering, deep learning), and experimental design.
• Experience with big data technologies (e.g., Spark, Hadoop) and database management (SQL, NoSQL).
• Excellent data visualization skills and experience with tools like Tableau, Power BI, or Matplotlib.
• Strong ability to translate complex scientific problems into solvable data science challenges.
• Exceptional communication and interpersonal skills, with the ability to influence and collaborate effectively across teams.
• Experience in a hybrid work environment and the ability to manage time effectively.

• Lead the design and execution of data science projects supporting scientific research initiatives.
• Develop and implement advanced statistical and machine learning models.
• Analyze large, complex scientific datasets to extract meaningful insights.
• Mentor and guide a team of data scientists and researchers.
• Collaborate with scientists and domain experts to define research objectives and analytical approaches.
• Identify and explore new data sources and analytical methodologies.
• Communicate complex findings clearly and effectively to both technical and non-technical audiences.
• Develop data visualizations and reports to illustrate key trends and results.
• Stay current with the latest advancements in data science, machine learning, and relevant scientific fields.
• Contribute to the development of scientific publications and presentations.

• Ph.D. or Master's degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related scientific discipline.
• Minimum of 7 years of experience in data science, with a significant portion focused on scientific research.
• Proven experience leading data science teams and projects.
• Expertise in machine learning algorithms, statistical modeling, and data mining techniques.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience working with large datasets and distributed computing frameworks (e.g., Spark).
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication, presentation, and interpersonal skills.
• Ability to work independently and collaboratively in a remote environment.
• Demonstrated experience in a scientific domain (e.g., bioinformatics, computational chemistry, experimental physics).