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Information Theory Jobs (NOW HIRING)

Stevens

Postdoctoral Researcher

Hoboken, NJ · On-site

$58K - $60K/yr

Expertise in quantum information theory, quantum optics theory or related fields. Please combine all required documents in one pdf file. The required documents are: Cover Letter CV Summary of ...

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How much do information theory jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for information theory in the United States is $30.46, according to ZipRecruiter salary data. Most workers in this role earn between $26.20 and $31.01 per hour, depending on experience, location, and employer.

What is information theory?

Information theory is a branch of applied mathematics and electrical engineering that studies the quantification, storage, and communication of information. It was founded by Claude Shannon in the 1940s and provides the mathematical foundations for data compression, transmission, and encryption. Information theory plays a crucial role in fields like telecommunications, computer science, cryptography, and even neuroscience, by helping to determine the most efficient ways to encode and transmit data while minimizing loss or error.

What are the key skills and qualifications needed to thrive as an information theorist, and why are they important?

To thrive as an Information Theorist, you need a strong background in mathematics, probability, and statistics, typically supported by an advanced degree in electrical engineering, mathematics, or computer science. Familiarity with programming languages such as Python or MATLAB and experience with specialized software for data analysis and simulation are often required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for conveying complex theories and collaborating on interdisciplinary projects. These skills are vital for developing innovative solutions to data compression, transmission, and security challenges in modern communications and technology.

What are the typical challenges faced by professionals working in information theory roles within industry or academia?

Professionals in Information Theory often encounter challenges such as translating abstract mathematical concepts into practical applications, especially when working on real-world communication systems or data compression projects. Collaboration with interdisciplinary teams—such as engineers, computer scientists, and data analysts—is common and requires strong communication skills to bridge theoretical and applied perspectives. Additionally, keeping up with rapid advancements in related fields like machine learning can pose a challenge, but also offers opportunities for impactful research and innovation. These roles frequently involve both independent problem-solving and teamwork, providing a dynamic and intellectually stimulating work environment.

What is the difference between Information Theory vs Data Scientist?

AspectInformation TheoryData Scientist
Required CredentialsMathematics, Electrical Engineering degreesStatistics, Computer Science degrees
Work EnvironmentResearch labs, academia, tech companiesBusiness, tech firms, startups
Industry UsageData compression, communication systemsData analysis, predictive modeling

Information Theory focuses on the mathematical foundations of data encoding and communication, often working in research or technical roles. Data Scientists analyze and interpret data to inform business decisions. While both roles involve data, Information Theory is more theoretical and specialized, whereas Data Scientists apply data analysis techniques in practical settings.

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Information Theory jobs near you
Infographic showing various Information Theory job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $63,360 per year, or $30.5 per hour.

Postdoctoral Fellowship in Electrical and Computer Engineering

Harvard University

Cambridge, MA • On-site

$67K - $91K/yr

Full-time

Re-posted 14 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

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82nd of 628 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral Fellowship in Electrical and Computer Engineering
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Computer Science
Position Description
The John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Department of Statistics at Harvard University seeks applicants for a postdoctoral fellow in Electrical and Computer Engineering.
This position is for a Postdoctoral Scholar in the area of information theory and artificial intelligence at the Harvard Information Theory Laboratory The successful candidate will work under the supervision of Prof. Flavio Calmon at Harvard SEAS. The postdoctoral researcher will develop information-theoretic methods for alignment, privacy, and reliability in modern AI systems.
Basic Qualifications
Applicants must have a PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related discipline, or be confident of its completion by the start of this position.
Additional Qualifications
Successful candidates will have publications in information theory and machine learning venues, such as IEEE Transactions on Information Theory, ISIT, NeurIPS, ICML, ICLR, and ACM FAccT. Experience in machine learning and information theory, and expertise in at least one of the following areas is preferred: AI alignment, (differential) privacy, and coding or information theory for AI systems. Proficiency in Python and experience with GPU cluster environments (e.g., SLURM) are a plus.
Special Instructions
Please provide a CV, a Research Statement, and two or more letters of recommendation.
The target start date is September 2026 (flexible). The position is funded for two years.
Contact Information
Sarah Gayer
Contact Email
sgayer@seas.harvard.edu
Salary Range
$67,600 - $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field
Minimum Number of References Required
2
Maximum Number of References Allowed
5
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