​The Research Institute of Medical and Health Sciences (RIMHS) is seeking to hire a dedicated postdoctoral research associate to investigate the mechanisms governing multi-organ pathologies in a mouse model of simulated microgravity. The successful candidate will be responsible for analyzing and interpreting OMIC data (genomics, transcriptomics, and epigenetics) generated by our research group and from publicly available biological databases. The Post Doc, under the supervision of the Principal Investigator, will dissect the gene regulatory networks associated with defects in skeletal muscle, liver, testes, brain, and other organs in mice under simulated microgravity. Laboratory expertise in handling and dissecting mice and basic techniques, such as RT-PCR, WB, gel electrophoresis, and microscopy, are also required. Transcripts must be submitted along with the CV in one document. ​

a)      Analyzing and interpreting OMICs data sets, including genomics, transcriptomics, and epigenetics data.

b)      Conducts bioinformatics analysis on genomics data

c)      Develop private and public biological genomic and proteomic databases

d)      Conceptualizing research projects and drafting manuscripts.

e)      Maintaining and handling laboratory mice.

f)       Maintaining laboratory logbooks and performing administrative tasks related to ordering reagents and preparing lab reports.

g)      Supervising graduate and undergraduate students and research assistants.

h)       Presents ongoing work and findings to colleagues​

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Preferred qualifications are underlined:
1.      Ph.D. in biomedical science with at least 1-3 years of experience in working with OMICs data sets demonstrated by at least one publication as a lead author in a top journal in the field of bioinformatics

2.      Experience in research and/or academic settings (published articles in the field of bioinformatics)

3.      Understanding of biological Data: DNA, RNA and protein sequences, expression, and structures

4.      Experience in the development of private or public biological databases

5.      Excellent organizational and documentation skills

6.       Able to work both independently and as part of a collaborative team

7.       Knowledge of biological data banks (e.g., NCBI, EMBL-EBI, Ensembl, KEGG, ENCODE)

Experience in statistical modeling.​