Postdoctoral Fellow - CausalML Lab

Johns Hopkins University; Baltimore (MD); On-site; USD 63,500 - 75,000; Full time

Benefits offered by this job

Total rewards package supporting health, life, career, and retirement

Job summary

The Chronicle Of Higher Education, Inc. is seeking highly motivated postdoctoral scholars for the CausalML lab at Johns Hopkins University in Baltimore. You will develop algorithms for causal decision-making, working closely with lab members.

The ideal candidate holds a PhD in a relevant field and possesses strong publication credentials. This full-time role offers an initial 12-month appointment, with potential for extension based on performance.

Qualifications

• PhD in Computer Science, Statistics, Electrical Engineering or related field.
• Strong publication record in peer-reviewed venues relevant to ML or AI.
• Strong understanding of fundamental causal inference and causal discovery algorithms.

Responsibilities

• Join the CausalML lab at Johns Hopkins University for research.
• Lead research projects independently from concept to implementation.
• Develop algorithms for causal decision-making using real-world datasets.

Skills

Algorithm development for non-IID or time-series data

Strong publication record in peer-reviewed venues

Understanding of causal inference and discovery algorithms

Proficiency in Python and deep learning

Teamwork skills in interdisciplinary environments

Education

PhD in Computer Science, Statistics, or related field

Job description

Overview

Johns Hopkins, founded in 1876, is America’s first research university and home to nine world‑class academic divisions working together as one university.

Salary

$63,500 - $75,000

Description

Dr. Murat Kocaoglu is seeking highly motivated postdoctoral scholars to join the CausalML lab at Johns Hopkins University in 2026. This position offers the opportunity to work directly with the 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 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

• CV
• Contact information for two references.

Equal Employment Opportunity Statement

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristics. The University is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors or demographic characteristics that are irrelevant to the program involved.

Pre‑Employment Information

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Background Checks

After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre‑employment background check including education verification. When deciding whether a candidate’s conviction history is job‑disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.

Vaccination Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID‑19 vaccine. This does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID‑19 vaccination and provide proof of vaccination status. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the seasonal flu vaccine or COVID‑19 vaccine (for SOM) requirement(s) may be provided to individuals with sincerely‑held religious beliefs or medical conditions that preclude them from receiving the vaccine.

Benefits

Johns Hopkins offers a total rewards package that supports our employees’ health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.