Job Description

Position Name:            Postdoctoral Researcher in Deep Learning and Network Science

Reports to:                    PrincipaI Investigator,

Location:                       Home-based, India

Application Deadline:  March 31, 2024

The successful candidate will be based in India as part of a multidisciplinary team of scientists and physicians, contributing to a portfolio of projects focused on leveraging network science, phylodynamics, and deep learning. The primary objective is to develop targeted HIV and hepatitis C virus (HCV) interventions for people who inject drugs in India (PWID).  

Preferred Education and Qualifications:

Have a Ph.D. in a subject area related to bioinformatics, machine learning, network science, or infectious disease modeling (e.g., Computer Science, Applied Mathematics, Statistics, Engineering, Infectious Disease Epidemiology, Genetic Epidemiology, etc.) and have significant experience with deep learning, as demonstrated by recent publications.

Experience analyzing large datasets and developing statistical and deep learning models (experience with network analysis and graph neural networks [GNNs] preferred).

Strong programming skills in Python and R.

Excellent communication and collaboration skills. 

Duties and Responsibilities:

Analyze longitudinal social and spatial network data, individual-level data, and HIV/HCV next-generation sequencing data.

Conduct biostatistical analyses using a range of analytical techniques, including regression, nonparametric methods, and machine and deep learning approaches.

Explore the use of graph neural networks (GNNs), for imputing and analyzing network data.

Develop and validate network models that simulate the effect of various network-based intervention strategies on disease incidence.

Conduct analyses in a command line environment on high-performance computing clusters, including bioinformatics pipelines.

Create and maintain systems for archiving analytical methods, results, and other research information, including protocols, documention, and code and software repositories.

Communicate research findings to scientific and lay audiences through publications, presentations, and other dissemination strategies.

Write statistical analysis sections for funding applications, research protocols, and manuscripts.

Desired Knowledge, Skills, and Abilities:

Applied knowledge of advanced biostatistical and bioinformatic methods with proficiency in multiple software packages and tools (e.g., BEAST, Jupyter, GitHub, NetworkX, PyTorch).

Excellent data management skills with proficiency in REDCap.

Familiarity with epidemiologic principles.

Strong data visualization skills. Experience generating figures for network and omics analyses preferred.

Ability to act proactively and independently, exercising good judgment, and thinking creatively to overcome data management and statistical analysis challenges.

Please email the following documents for consideration to msalvat4@jhu.edu, indicating “Postdoctoral Researcher in Deep Learning and Network Science” in the subject line:

Curriculum Vitae

Cover Letter detailing your interest in the role and your expertise in deep learning, bioinformatics, and/or network science

Three to five references

We will review applicants weekly and the position will close when filled, hence candidates are advised to apply as early as possible.

About Company

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