JMP 2027 Summer Internship; Causal Inference (Master's/Phd)

Аналитика рынка

Стек

Бесплатно. Вход по почте.

Откликнуться

Загрузите резюме — мы свяжем вас с работодателем напрямую через нашу базу.

Описание

Job Description Looking for *that* internship? The game-changing one that will help you learn, grow, and chart your path forward? You’ll find it at JMP (a subsidary of SAS)! Our interns aren’t coffee runners – they do real, meaningful work. Our award-winning internship program is focused on development, culture, and community. We’ll help you grow professionally, find (or further) your passion, and make memorable connections that last beyond the summer. The JMP Life Sciences division improves all JMP products with advanced solutions in a wide number of fields, including causal inference, survival, genomics, clinical data science, and chemistry. We are also spearheading new developments for cutting edge implementations using modern LLMs, agentic design, context engineering, UI design, PyTorch, and XGBoost. As an intern on the JMP Life Sciences team, you may: Program in R/Python/C++ or other proper coding language to build new/state-of-art causal inference workflows/methods. Explore algorithms that can be adopted to JMP, such as causal discovery, causal machine learning, LLM-based, or other cutting-edge methods. Test, benchmark, document, and promote this work (written and/or video). What we are looking for: You are pursuing a Master’s or preferably a PhD in Statistics, Biostatistics, Computer Science, Data Science, Economics, Engineering, or other life-science-analytic focused major, not graduating prior to December 2027. Strong knowledge about causal inference. Knowledge about

Полное описание, компания и ссылка на вакансию — после входа. Войти

Контакты работодателя (email/phone/telegram) скрыты из публичного превью — отправьте резюме, чтобы мы связали вас напрямую.