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The Barman laboratory has an immediate opening for two (02) postdoc associate positions. The details of the positions are given below.
Position 1: One fellowship is available in the area of optical imaging nanoprobes for biomedical applications.
Research Theme: The research in the laboratory focuses on developing advanced nanoprobes/plasmonic substrates with functionalities tailored toward nanoplasmonics, biosensing, and targeted molecular imaging. Further, translating them into clinical applications and driving them toward commercialization for improving healthcare.
Required Qualifications/Education:
- Applicants must hold a Ph.D. in optical engineering, chemistry, bioengineering, biophysics, nanotechnology, or other related fields.
- This fellow position is most suitable for a motivated individual with leadership qualities and a commitment to take on more independent obligations while working as part of a multidisciplinary research team.
Required Skills and Abilities:
- Candidates should have a solid experimental research background knowledge in Raman spectroscopy; surface-enhanced Raman spectroscopy (SERS); DNA nanotechnology; plasmonics; nanofabrication; and design and development of novel multifunctional nanoprobes.
- Prior experience with pre-clinical research using mammalian cells and tissues is preferable.
- Excellent scientific writing and communication skills
- Ability to work efficiently and collaboratively manner with others.
- A high level of productivity for publishing in peer-reviewed publications.
Position 2: A second postdoc fellow for developing and using artificial intelligence (AI) and machine learning analyses.
This position is available to work for developing and applying artificial intelligence (AI) and machine learning analyses to focus on a broad range of biological problems. Our lab works on developing new technologies for studying complex biological systems through advances in nanomaterials, optics, and artificial intelligence. For example, researchers collect sizeable Raman spectroscopy data and label-free quantitative phase imaging datasets of biomolecules, cells, and tissues. Computational methods will be necessary to annotate and analyze those datasets and relate function and structure to improve and transform images into scientific discoveries. The laboratory invites candidates to join us in developing methods with real-world applications necessary to enhance our biology understanding further.
Applicant’s job responsibilities:
- To build machine learning models in Python using standard machine learning libraries.
- Building and training supervised machine learning models (prototypes) for prediction and binary classification tasks involving multiple linear regression, logistic regression, neural networks, and decision trees.
- Tracking and event finding in 2D and 3D movies.
- Segmentation and classification of biological structures.
- Working and collaborating with an interdisciplinary team and researchers.
- Processing of vast datasets.
Required Education: candidate must have-
- Ph.D. Degree in Computer Science, Statistics, Machine Learning, Computational Biology, or any other related field.
- Advanced knowledge of Statistics, Calculus, Data Structures, Machine Learning, and Algorithms.
Skills and Abilities:
- Strong background knowledge in machine learning, computer vision, and deep learning.
- Good experience with deep-learning frameworks, large optical microscopy datasets, MATLAB, and Python.
- Enthusiasm for utilizing computational approaches to learn to discover biological insights
- Good publication track record.
- Outstanding scientific writing and oral communication skills,
- An ability to work efficiently and collaboratively in a self-directed manner.
- A high level of throughput for peer-reviewed publications is expected.
Application Procedure: Interested eligible candidates should send an updated CV (including publications), a cover letter encompassing a brief description of qualifications, experience, and interests, and contact information for three individuals (referees) who can offer letters of reference upon request to the following: ibarman@jhu.edu
Deadline: Applications should be received for full consideration by January 17, 2023. Applications submitted before the deadline will be considered first. The expected start is as soon as possible after the deadline.
Additional information about the group, including a complete list of publications and research areas, can be found in the link below.
Quick Overview
| Type: | Postdoctoral |
| Location: | United States |
| Fellowship Amount: | As per University Regulations |
| Eligibility: | PhD |
| Email: | ibarman@jhu.edu |
| Other Info: | Visit Website |
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