Fellowship Jobs

21,577 open positions · Updated daily

Fellowship positions sit at the intersection of research and industry, offering a unique blend of hands‑on project work and academic rigor. 2024 has seen a surge in funding for AI, data‑driven health, and climate science fellowships, with more than 2,100 roles available that combine stipend, tuition waiver, and research grants.

Common fellowship titles include Data Science Fellow, AI Research Fellow, Computational Biology Fellow, and Quantitative Analyst Fellow. Responsibilities range from developing end‑to‑end ML pipelines in Python and PyTorch, publishing peer‑reviewed papers, to presenting findings at SIGGRAPH, NeurIPS, or ISMB conferences. Fellows often collaborate with cross‑functional teams in product, policy, and regulatory groups.

Transparent salary information is critical for fellows because funding streams vary widely—stipends can differ by host institution, grant size, and year. Knowing exact pay, benefits, and equity options enables fellows to compare opportunities, plan long‑term career trajectories, and negotiate grant support more effectively.

Pharmacy Services Manager

Company: Houston Methodist Hospital

Location: Houston, TX

Posted Oct 06, 2025

Assists the Director in maintaining integration of pharmacy services throughout the entity to ensure compliance with legal requirements set by federal, state,…

Frequently Asked Questions

Typical salary ranges by seniority
Entry‑level research fellows usually receive an annual stipend of $45,000–$75,000 plus health insurance. Mid‑level data science fellows or post‑docs earn $70,000–$110,000 and may receive partial tuition coverage. Senior or principal fellows, especially in industry or high‑profile grant programs, can command $100,000–$160,000 plus performance bonuses and intellectual‑property revenue sharing.
Required skills and certifications
Key skills vary by specialty but commonly include: Python, R, SQL, and statistical libraries (pandas, scikit‑learn); ML frameworks such as TensorFlow, PyTorch, or JAX; cloud platforms like AWS SageMaker, GCP AI Platform, or Azure ML; and version control with Git. Certifications that boost candidacy include TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, and Certified Analytics Professional (CAP). For AI fellowships, expertise in NLP (transformers, BERT), reinforcement learning, or computer vision is essential, often supported by coursework such as Stanford CS231n or MIT 6.034.
Remote work availability
Remote availability varies by program. Approximately 70% of fellowship listings allow full remote or hybrid collaboration, especially those hosted by universities or cloud‑based research labs. Industry fellowships at companies like Google, Microsoft, or NVIDIA often require on‑site presence for lab access, but many are transitioning to hybrid models. Applicants should verify remote policies in the job description or contact the program coordinator directly.
Career progression paths
Career paths after a fellowship typically follow: Fellow → Post‑doctoral Fellow → Senior Fellow/Principal Fellow → Lead Research Scientist → Director of Research. In data‑science tracks, a fellow may progress to Data Scientist → Senior Data Scientist → Lead Data Scientist → Chief Data Officer. Timing depends on publication record, grant success, and leadership roles; most fellows advance within 3–5 years of completing their fellowship.
Industry trends for Fellowship
Current trends driving fellowship demand include: AI ethics and responsible AI research, which has spurred fellowships at institutions like MIT Media Lab and IBM Research; interdisciplinary health‑tech fellowships focused on AI for diagnostics, funded by NIH and DARPA; climate‑modeling fellowships leveraging high‑performance computing; and open‑source software fellowships that contribute to platforms such as TensorFlow, PyTorch, and Apache Spark. These trends increase funding opportunities and collaborative networks across academia and industry.

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