Join us!

Why join?

We work on better understanding observational data, motivated by real problems in healthcare. For researchers interested in working with challenging real-world data, our collaborations with clinicians at Columbia University and other institutions allow for unique access to patient data along with the opportunity to have a tangible impact on patient care.

We are funded by NSF, NIH, and the James S. McDonnell Foundation.

Key ongoing projects include:

  • Inference under uncertainty: how can we learn from data where the timing of events or value of variables can't be trusted?
  • Causal inference and explanation with prior knowledge: We aim to make better use of prior inferences and domain knowledge, while being robust to cases where this may be wrong or inapplicable.
  • Causality in complex systems: We're developing methods for causal inference across time and space, at multiple scales. The project includes better understanding nonstationarity and the evolution of causality over time, and expanding causal inference beyond variables to understand causes for changes in system properties.
  • Mobile health/device development: Recognizing when, what, and how much people eat from body-worn sensors (audio and motion). We are working on automating calorie counting and developing unobtrusive devices to do this.

Open positions

Postdoc | Programmer | Grad student | Undergrad

Postdoctoral researchers

Candidates are sought with expertise in a subset of the following areas:
-Causal inference
-Analysis of time series data
-Biomedical informatics
-HCI and activity recognition
-Sensor and device development

Requirements include at least one publication in a major AI or ML conference (e.g. IJCAI, AAAI, ICML, NIPS, UAI) along with a PhD in Computer Science or a related field.

Initial appointments will be for one year, but funds are available for further renewal.

To apply, please send a statement of interest, cv, 2-3 representative publications, and email addresses for 2-3 references to samantha.kleinberg@stevens.edu

Programmer/research staff

We are looking for full time staff members who are passionate about advancing research, as well as developing and maintaining software. This position is ideal for someone with an MS or industry experience who would like to be involved in academic research and who is detail oriented.

An MS in Computer Science, Data Science, or a related field is preferred, but is not required for candidates with industry experience. Evidence of well-documented and maintained code is required. Python and Lisp experience are a plus. Initial appointments will be for one year, but funding is available for longer, and positions may continue long-term. Title and duties are negotiable.

To apply, please send a brief summary of your interest and experience, resume or cv, 2-3 code artifacts, and email addresses for 2-3 references to samantha.kleinberg@stevens.edu

Graduate students

We are seeking PhD students interested in the intersection between theory and application. If you're looking for a lab, email your CV and why you think it's a good fit and we can set up a time to talk.

Undergraduate researchers

If you are a current Stevens undergraduate student interested in an independent study or summer research experience, email (samantha.kleinberg@stevens.edu) with a brief description of your prior research experience (it's ok if you don't have any!) and what you're looking to get out of a research project.