AI.MED Postdoctoral Scientists

University of Alabama at Birmingham
Birmingham, AL
Closing date
Apr 4, 2023

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Organization Type
Multiple postdoctoral or staff scientist positions at UAB's Planned interdisciplinary AI-enabled Drug Discovery Initiative

Supervisor: Jake Y. Chen, Ph.D. FACMI, FAIMBE, Professor of Genetics, Computer Science, and Biomedical Engineering; Director of the ai.MED laboratory; Chief Bioinformatics Officer, the Informatics Institute, the University of Alabama at Birmingham; Birmingham, AL.

Dr. Chen is an international expert in translational bioinformatics and computational drug discovery. In the past 25 years, he has worked in the biotech industry and Academia to perform R&D in biological data mining and systems pharmacology, with nearly 200 peer-reviewed publications and 200 presentations worldwide. In 1998, he worked at Affymetrix, Inc. to design the world's first DNA microarrays to map the human and mouse transcriptome. In 2007, he founded the Indiana Center for Systems Biology and Personalized Medicine to refine the team research agenda for multi-omics-based precision medicine. In 2016, he launched AI.MED laboratory at UAB to integrate bioinformatics, clinical informatics, translational medicine, genomics, and AI to explore solutions in precision oncology. In 2023, he will establish a new "disruptive" interdisciplinary center to bring together teams from basic research, informatics, IT, clinical medicine, and drug discovery organizations to accelerate drug discovery. He is recognized for his academic leadership, entrepreneurship experience, and contribution to translational biology and systems biology. He is the past President of the Midsouth Computational Biology and Bioinformatics Society (HTTP:// and known for organizing the Biological Data Mining and Knowledge Discovery Workshop (BIOKDD) for more than two decades at the ACM's flagship data science conference KDD annually. He is an elected fellow of the American College of Medical Informatics (ACMI), the American Institute of Medical and Biological Institute (AIMBE), and the American Medical Informatics Association (AMIA). He serves on the editorial boards of BMC Bioinformatics and JAMIA, and is a frequent panelist at the NIH/NSF on systems biology, big data, and AI research. He is an ACM distinguished member and serves on the board of ACM's Special Interest Group on Computational Biology (SIGBIO). In 2019, he was recognized by Deep Knowledge Analytics as one of the "Top 100 AI Leaders in Drug Discovery and Healthcare". He is also a passionate mentor, recognized as the three-time finalist of Indiana's MIRA Award on "Technology Mentors of the Year", for transforming the careers of hundreds of trainees into various data science careers in the past two decades.

We are recruiting talented bioinformatics, AI/ML, and data scientists nationally and internationally to join us in forming a new disruptive AI-enabled drug discovery center, iCADD. iCADD will represent a broad partnership of AI.MED laboratory(HTTP:// that Dr. Chen founded in 2016, the UAB Informatics Institute (HTTP://, the UAB Center for Translational and Clinical Sciences (CCTS, HTTP://, the O'Neal Comprehensive Cancer Center (CCC, HTTP://, the UAB Precision Medicine Institute (PMI, HTTP://, the UAB Bill L. Harbert Institute for Innovation and Entrepreneurship (HTTP://, and Southern Research (HTTP:// located next to the UAB campus. iCADD aims to disrupt the future of drug discovery by making drugs faster, better, cheaper, and more tailored to individual patient conditions. Towards this end, we will develop and use software tools, databases, workflows, team data science, and clinical trials that synergizes genome biology, precision medicine, and learning healthcare. We work with a wide variety of data sets/streams collected, including single-cell transcriptomics, multi-omics data, biomolecular networks, literature-mined knowledge graphs, ontology, pathology/radiology imaging, electronic health records, epidemiology, real-world pharmaco-surveillance data, patents, and social media. We will use cloud-enabled workflows and pipelines from open-source repositories and subscription-based software systems to perform innovative queries that examine candidate drugs' bioactivity profile, structure-activity profile, safety, and efficacy on specific disease cohorts. In particular, AI.MED laboratory has innovative technology platforms that advance the frontiers of drug repositioning, companion diagnostic discovery, and digital twins--essential technology components for AI-enabled drug discovery.

The selected postdoctoral or staff researcher will be able to work in a multidisciplinary team--in an "Academia-startup" hybrid cultural environment--to study drug discovery creatively for complex human diseases, including cancer, autoimmune diseases, Alzheimer's disease, diabetes, and psychiatric disorders. This flexibility gives the person a unique entrepreneurial experience to consider the "Industry-Academia" dual career track, with training on high-profile publications, grant writing, conference presentations and business plan writing, drug discovery market analysis, and fundraising. The scientist will learn how to develop, apply, and "sell" state-of-the-art AI and machine learning techniques to analyze multi-omics data without learning the comforts of an Academic environment. A particular advantage of our infrastructure is the ability to perform translational bioinformatics analysis with patient cohorts, along with fully "live" electronic medical records--all using a team data science platform called U-BRITE (HTTP:// that Dr. Chen leads at UAB. We collaborate extensively with UAB's Center for Clinical and Translational Sciences (CCTS), O'Neal Comprehensive Cancer Center, Precision Medicine Institute, Division of Clinical Immunology and Rheumatology of the Department of Medicine, Computer Science Department, and Biomedical Engineering Departments, and the UAB School of Public Health and School of Business.

An ideal candidate may come from AI/ML, bioinformatics, CS, biostatistics, biomedical engineering, or other biomedical data science backgrounds. Candidates should be proficient with R/Python/Julia/SQL/MATLAB programming languages and have experts in developing algorithms using Github and cloud-based computing platforms for data-intensive applications. Expertise in analyzing genomic and functional genomic data is required, with supporting evidence through peer-reviewed high-quality publications. Good English communication skills, including technical writing and oral presentation, are expected. We are particularly interested in candidates with one or more first-author publications in the following areas: 1) integrative bioinformatics multi-omics analysis of genes, drugs, and diseases; 2) systems pharmacology and network biology methodology development, using algorithmic, statistical, machine learning, and software development techniques, to build protein-ligand binding models, molecular interaction networks, drug-gene signatures, or literature-extracted knowledge graphs; 3) development of late-breaking AI/ML, mathematical, data science, and engineering models that enable the dynamical models of drug perturbation effects of parameterized complex systems in virtual humans.

In this position, the trainee will receive world-class training to become a leading researcher in translational bioinformatics and applications of AI/data science in precision medicine. The trainee will interact with multidisciplinary researchers in the Schools of Medicine, Public Health, Engineering, Science, and Business to research selected topics funded by NIH and the NSF. The trainee will be encouraged to attend and present at international meetings and workshops that Dr. Chen organizes in the field throughout the year, e.g., MCBIOS, BIODD/KDD, AMIA Annual Symposium, ISMB, and other IEEE/ACM Conferences on Bioinformatics. The trainee will perform primary bioinformatics and computational biology research, leading to first-author and co-authorship publications. The trainee will also have opportunities to learn grant writing, mentor undergraduate/graduate student, guest lecture in courses, and prepare his/her path toward an independent research career.

Upon approval, exceptionally well-qualified candidates with a proven track record of practice goal-setting and accomplishment may work remotely full-time or part-time, subject to the rules and regulations of UAB and a remote work management plan with Dr. Chen.

Postdoc Benefits: Competitive postdoc salary will be provided according to the NIH postdoc salary scale. In addition, all postdoctoral scholars will qualify for an outstanding UAB postdoc benefit package, including health, life, and other insurances, the university's 403(b) program, and enjoy vacationing, sick leave, maternity/paternity leave, and other benefits. Candidates may also request additional expense account for awards up to $5000 for relocation expense, conference travel, and equipment purchase. Outstanding biomedical computing infrastructure and support will be provided through the UAB Biomedical Research Information Technology Enhancement (U-BRITE) platform through the Informatics Institute. UAB is an Equal Opportunity/Affirmative Action Employer committed to fostering a diverse, equitable, and family-friendly environment.

Staff Benefits: In addition to a permanent full-time position, UAB offers a competitive salary and a highly competitive plan, including a retirement package/pension to all staff scientists.

To apply, please email Dr. Jake Chen ( with a cover letter highlighting relevant experience and qualifications, a current CV, and the contact details of three references. The application will be reviewed upon receipt monthly.

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