Postdoctoral Fellow - CausalML Lab

Dr. Murat Kocaoglu is seeking highly motivated postdoctoral scholars to join CausalML lab at Johns Hopkins University in 2026. This position offers the opportunity to work directly with CausalML Lab (led by Dr. Kocaoglu), alongside its respective lab members.

The research focuses on developing fundamental algorithms for causal decision making using real-world, non-IID time series datasets. This work is primarily conducted at the Homewood Campus in Baltimore. The ideal candidate has experience with developing algorithms for non-IID or time-series data.

Applicants with strong credentials and motivation should still apply even if they lack these specific qualifications. This is a full-time position with an initial appointment duration of 12 months, and the possibility of further extension based on performance and funding.

Qualifications

• PhD in Computer Science, Statistics, Electrical Engineering or a related field.
• Strong publication record in peer-reviewed venues (e.g., NeurIPS, ICML, UAI, ICLR, AAAI, AISTATS) relevant to ML or AI.
• Strong understanding of fundamental causal inference and causal discovery algorithms.
• Experience with the design, development and implementation of causal ML algorithms.
• Ability to lead research projects independently from concept to implementation.
• Capability to formulate research methodologies and manage project timeline.
• High proficiency in Python and deep learning frameworks (e.g., PyTorch).
• Excellent teamwork skills for working in an interdisciplinary environment involving engineers, computer scientists, and clinicians.
• Ability to work effectively in a highly collaborative, multi-lab environment.

Application Instructions

Applicants must submit the following documents via this Interfolio posting:

• CV
• Contact information for two (2) references.