Fellowship Jobs in Multiple Locations

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.

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 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 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.

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.