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Join the Barman Lab

Welcome to the Barman Lab for Photonics in Quantitative Biology and Medicine! In this lab, we study a variety of pathophysiological conditions, with the core elements of using optics, nanomaterials and machine learning to gain a better understanding of human health.

We are always looking to recruit bright, energetic, and highly motivated individuals on our exciting journey. Should you harbor an interest in being a part of our research endeavors, we encourage you to send your application materials including your CV and cover letter to: [email protected]. Opportunities are available for researchers (national and international) at the undergraduate, graduate, and postdoctoral levels in different projects.

Location

PROF. BARMAN'S OFFICE ADDRESS:
  • Office
  • Room 103, Latrobe Hall 3400 N. Charles St. Baltimore, MD 21218
LAB & SHIPPING ADDRESS:
  • 217, Latrobe Hall
    3400 N. Charles St.
    Baltimore, MD 21211

Scientific progress is enhanced and accelerated when diverse perspectives are brought to bear on hard problems. The Barman laboratory respects, values, and celebrates diversity. The PI and each member of the lab take pride in fostering an inclusive environment that attracts trainees of different ethnicity, race, sexual orientation and gender and backgrounds, and allows them to thrive, grow, and excel.

Open Position – 1

The Barman laboratory at Johns Hopkins University has an immediate opening for a postdoctoral fellow position in the field of optical imaging nanoprobes for biomedical applications. The research focus of this position will be the development of advanced nanoprobes/plasmonic substrates with functionalities tailored toward biosensing, nanoplasmonics, and targeted molecular imaging. Further, translating them into clinical applications and if possible, driving them toward commercialization for improving healthcare.

This academic position is most suitable for a driven individual with leadership goals, and a willingness to take on more independent responsibilities while working as part of a multidisciplinary research team.

Education:

Applicants must hold a Ph.D. in chemistry, optical engineering, bioengineering, biophysics, nanotechnology, or related fields.

Skills and Abilities:

Strong experimental research background in Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), plasmonics, DNA nanotechnology, nanofabrication, and/or design and development of novel multifunctional nanoprobes are encouraged to apply.

Experience with pre-clinical research using mammalian cells and tissues is preferred.

Excellent scientific writing and oral communication skills, as well as the ability to work effectively and collaboratively in a self-directed manner with others.

A high level of productivity for peer-reviewed publications is expected.

Open Position – 2

The Barman laboratory at Johns Hopkins University is looking for a postdoctoral fellow for the development and application of artificial intelligence and machine learning analyses to address a wide range of biological problems. Our lab works on the development of modern technologies for the analysis of complex biological systems via advances in optics, nanomaterials, and artificial intelligence. We collect large Raman spectroscopy and label-free quantitative phase imaging datasets of cells, tissues, and biomolecules. Computational methods will be needed to annotate and analyze those datasets, as well as to relate function and structure, to help transform images into scientific discoveries. We invite you to join us in developing methods that have real-world applications and are necessary to further enhance our understanding of biology.

Applicant’s job responsibilities will include:

Build machine learning models in Python using popular machine learning libraries.

Build and train supervised machine learning models for prediction and binary classification tasks, including multiple linear regression, logistic regression, neural networks, and decision trees.

Unsupervised, weakly-supervised, and interactive learning.

Segmentation and classification of biological structures.

Tracking and event detection in 2D and 3D movies.

Processing of very large datasets.

Working with an interdisciplinary team and collaborating with experimentalists.

Education:

PhD in Computer Science, Machine Learning, Statistics, Computational Biology, or a related field.

Advanced knowledge of Machine Learning, Statistics, Calculus, Data Structures, and Algorithms.

Skills and Abilities:

Strong background in computer vision, machine learning, and deep learning.

Experience with large optical microscopy datasets, deep-learning frameworks, Python, and MATLAB.

Enthusiasm for using computational approaches to learn to discover biological insight.

Strong publication track record.

Excellent scientific writing and oral communication skills, as well as the ability to work effectively and collaboratively in a self-directed manner with others.

A high level of productivity for peer-reviewed publications is expected.

 

Interested candidates should send a CV (including publications), a cover letter containing a brief description of their research experience and interests, and contact information for three individuals who can provide letters of reference upon request to:  [email protected]

To ensure full consideration, applications should be received by January 4, 2023. Applications submitted earlier than this date will be considered first. The expected start is as soon as possible after the closing date.