Dr. Chen is an international expert in translational bioinformatics and biomedical data science research. He has over 25 years of R&D experience in biological data mining and systems biology, with over 170 peer-reviewed publications and 200 presentations worldwide. He was the founder of Indiana Center for Systems Biology and Personalized Medicine at Indiana University – Purdue University Indianapolis, and precision medicine companies including Predictive Physiology and Medicine and Medeolinx, LLC. He is currently President-elect of the Midsouth Computational Biology and Bioinformatics Society and an elected fellow of the American College of Medical Informatics. He serves on the editorial boards of BMC Bioinformatics and Journal of American Medical Informatics Association. In 2019, he was recognized by Deep Knowledge Analytics as one of the "Top 100 AI Leaders in Drug Discovery and Healthcare" and three-time finalists of Indiana's MIRA Award on "Technology Mentors of the Year".
Dr. Chen's ai.MED laboratory(aimed-lab.org), founded in 2016 at the UAB Informatics Institute (informatics.uab.edu/) of the School of Medicine, has been developing informatics, data science, and engineering methods and software tools to understand and transform future biology, medicine, and healthcare. We work with a variety of data sets, including single-cell genomics, RNA-sequencing, public biological knowledgebases, including PubMed, PubChem, and GEO. We are well funded to study complex human diseases, including cancer, autoimmune diseases, Alzheimer's disease, diabetes, and psychiatric disorders. We develop and apply state-of-the-art AI and machine learning techniques to analyze multi-omics data. A particular advantage of the ai.MED laboratory at UAB Informatics Institute is the ability to perform bioinformatics analysis with patient electronic medical records. UAB Informatics Institute is the hub for biomedical data science primary research, education, infrastructure development, and service on campus, with nine core faculty and more than 30 affiliate faculties. 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 Department.
We are seeking skilled and motivated postdocs to join our interdisciplinary team of bioinformatics, data science, precision medicine, and AI researchers. An ideal candidate may come from diverse biomedicine/healthcare-related data science backgrounds, including but not limited to bioinformatics, cancer genomics, computer science and engineering, data science, statistical genomics, and biomedical engineering. Candidates should be familiar with R/Python/Java programming language, and experience in developing computational methods using Github and data science tools for biological, medical, or healthcare 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.
The various positions will have a different emphasis on one or more of the following areas: 1) bioinformatics data analysis, using next-generation sequencing data, single-cell genomics, for cardiovascular disease, cancer, diabetes, and autoimmune diseases; 2) systems biology and network biology methodology development, using algorithmic, statistical, machine learning, and software development techniques, to extract, mine, predict, and interpret molecular interaction or literature-extracted knowledge graphs in collaboration of biomedical and translational researchers in the School of Medicine; 3) Next-generation AI systems, using late-breaking mathematical, data science, and engineering approaches, to address grand challenge problems in data-driven precision medicine/healthcare problems of the future.
In this position, the trainee will receive world-class training to become leading researchers 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 both first-author publications 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 towards an independent research career.
During the COVID-19 pandemic, we will request an exception for recruited postdocs to work remotely at the home office. Upon approval up to approval, the postdoc may remain the current location, as long as he/she obeys the full-time rules and regulation of UAB and the ai.MED for work reporting during this unusual time.
Postdoc Benefits: Competitive postdoc salary will be provided according to the NIH postdoc salary scale. In addition, all postdoctoral scholars will qualify for 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, ubrite.org/) platform that Dr. Chen leads at the Informatics Institute. UAB is an Equal Opportunity/Affirmative Action Employer committed to fostering a diverse, equitable, and family-friendly environment.
An ideal candidate may come from diverse biomedicine/healthcare-related data science backgrounds, including but not limited to bioinformatics, cancer genomics, computer science and engineering, data science, statistical genomics, and biomedical engineering. Candidates should be familiar with R/Python/Java programming language, and experience in developing computational methods using Github and data science tools for biological, medical, or healthcare 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.
To apply, please email Dr. Jake Chen (email@example.com) with a cover letter, current CV, and contact details of three references. The application will be reviewed upon receipt, and candidates will be interviewed monthly until all the positions are filled.