Position and Address Professor Dept. of Computer Science and Engineering Islamic University, Kushtia-7003, Bangladesh Ph: +88-02477786704 (Off.) Cell: + 8801717127758 Fax: +88-02477786705 (Off.) E-mail: [email protected]; [email protected] Website: https://iu.ac.bd/index.php/site/dept_mainmenu/CSE/30 Linkedin:https://www.linkedin.com/in/habibcseiu/ ResearchGate:https://www.researchgate.net/profile/Md-Habibur-Rahman-2 Google Scholar: https://scholar.google.com/citations?user=DzAiISMAAAAJ&hl=en Qualification Summary • Ph.D.in Bioinformatics and Machine Learning with a background in Computer Science and Engineering and experience with potential areas of research that include Bioinformatics, Machine Learning/AI, Bioengineering, High-throughput Next Generation Sequencing, System Biology, Biostatistics, Biomedicine. Biomedical Informatics, Computational Biology, Human Genetics, Genomics, Transcriptomics, Proteomics, Multi-omics, and/or related fields. • Previous experience working on Psychiatric disorders, Neurodevelopmental disorders, Neurodegenerative and Neurological Disorders, Cardiovascular diseases, Autoimmune diseases, Type 2 diabetes, Obesity, Cancers, COVID-19, Idiopathic pulmonary fibrosis, Metabolic disorders, Mucormycosis, Chikungunya co-infection, HIV co-infection, Lumbar Spondylosis, Postoperative cognitive dysfunction, Polycystic ovarian syndrome (PCOS), Female infertility, etc. and understanding of basic molecular biology. • Desired skills include proficiency in statistical computing (with R, C, Matlab, or Python), and expertise in some of the following areas: (1) Bioinformatics and Sequence analytical tools and pipelines (2) Machine learning (3) Survival analysis (4) Molecular technique in gene functional analyses. • Familiarity with bioinformatics databases and resources available (i.e. TCGA, GTEx, NCBI, EBI, etc) for bioinformatics analyses and pipelines using Bioconductor packages (limma, edgeR, DESeq2, ROC, etc.) and/or similar statistical programming language. • Hands-on experience in analyzing data from GWAS and next-generation sequencing technologies such as GWAS, whole-exome, whole-genome, RNASeq/Single-cell Seq, lncRNA-Seq, ChIP-seq, Methyl-seq, and miRNA-seq, etc. • Experience with molecular docking and dynamics simulation, virtual screening, and ligand design in drug discovery. • Strong experience in deep learning research and working experience with TensorFlow, PyTorch, SciKit, and other related ML/DL tools. • Fluency in R, Python, UNIX shell, overleaf, and/or LaTeX and familiarity with standard software packages related to next-generation sequencing, genetics, and genomics. • Self-motivated with a proven record of scientific publications in high-quality peer-reviewed scientific journals, the ability to prepare manuscripts for publication in top-tier journals, the ability to work independently and in a collaborative and interdisciplinary research environment, and the ability to work under limited supervision. • Grant writing experience. Ambition to write grant proposals and to seek new grants to further develop an interdisciplinary research topic. • Experience in supervising graduate and undergraduate student research and teaching. • Excellent problem-solving and organization skills and Effective oral and written communication skills. Research Goal Research goals are involved but are not limited to: • The primary goal is to carry out bioinformatics and computational analysis to identify genes associated with the risk of complex genetic diseases using high-throughput sequencing data. • To develop and apply bioinformatics, statistical, machine learning, and deep learning methods to solve health science problems in transcriptomics, genetics and genomics, and medical data analytics. • To develop novel computational strategies to identify biologically important functional pathways. • To undertake a multimodal approach to analyze a variety of datasets from state-of-the-art techniques, such as whole-genome sequencing, whole-exome sequencing, GWAS, RNA-Seq, Single-cell Seq, lncRNA-Seq, ChIP-Seq, Methyl-Seq, and miRNA-Seq, etc to understand gene interactions in metabolic diseases and cancer. • To understand the key concepts in molecular biology in the development of various diseases in order to potentially identify novel targets and develop new treatment strategies for the advancement of science. Skills and Background Knowledge Programming Language: Python, R, Matlab, Java, C, C++, SQL, JavaScript, HTML, CSS, Shell Script etc. Deep Learning Tools: Scikit-learn, Caffe, Pytorch, TensorFlow, Keras, Pandas, Numpy, Scipy, OpenCV etc. Software Tools: MS Office, Adobe Photoshop, Adobe Illustrator, EnrichR, DAVID, GREIN, BioJupies, MySQL, Oracle, Cisco Packet Tracer, AutoDock, PyRx, Chimera, Swiss PDB Viewer, Avogadro, Biovia Discovery Studio, Ligplot, Gromacs, etc. Awards & Honors 2016–2020 CAS-TWAS President’s Fellowship, University of Chinese Academy of Sciences, Beijing, China.