Post-Doctoral Positions at the NIH, Framingham, Massachusetts (USA)

2 Post-Doctoral Positions at the NIH

The Population Sciences Branch (PSB) of the National Heart, Lung, and Blood Institute (NHLBI) at the National Institutes of Health invite applications for 2 Post-Doctoral Fellow positions in Dr. Andrew Johnson’s Lab. Dr. Johnson is a tenured NIH Senior Investigator with stable funding, and a research lab based at the historic Framingham Heart Study (FHS). The FHS was started in 1948 with a focus on unlocking the risk factors behind cardiovascular disease. The Johnson Lab is highly focused on understanding platelets and their role in both bleeding and cardiovascular disease, and how we may improve anti-platelet therapeutics. Trainees in the Johnson Lab have gone onto successful careers in industry and academia, and the Lab has >20,000 citations to its work with a current h-index >70.

We seek motivated, creative and bright individuals, to work at the Framingham Heart Study. The FHS, has a wealth of genetic and OMICs data including whole genome sequence data, transcriptomes (microarray and RNA-seq), methylome, lipidome, metabolome, microbiome and proteome. Additionally, the Johnson Lab has led the collection of the largest global samples to date on platelet function and platelet reactivity, both within FHS and other cohort samples. Relevant future research project areas for Fellows include the genetics of platelet function, pharmacogenetics of anti-platelet therapy, integration of platelet transcriptome and other OMICS data with cardiovascular risk and platelet function data, risk prediction of cardiovascular disease based on platelet biomarkers, and the relationship between platelet biomarkers and clinical bleeding history. Additional epidemiological questions relate to how platelets change in aging, ethnic differences in platelet function, the influence of platelet function on cancer risk, and the role of physical activity, dietary intake and other environmental factors on platelet function.

We collaborate widely with several Domestic and International Consortia in the area of Hematology (cell counts), Hemostasis (clotting factors), and cardiovascular risk (MI, stroke, VTE). We are co-leading genetic projects on platelet counts in ~1.2 million individuals in sample size to generate new target genes controlling platelet biogenesis and decay. We partner with stem cell collaborators, zebrafish and mouse geneticists for functional studies to follow up human platelet genetic discoveries.

Applicants must have an M.D. and/or Ph.D. and research experience in 1 or more of the following: Epidemiology, Hematology, Platelet Biology, Statistical Genetics, Genomics, Pharmacogenomics, and/or Bioinformatics. A proven track record of prior publications is expected.

The successful candidate will be offered a competitive salary commensurate with experience and qualifications. The initial appointment will be for a minimum of 2 years, with appointment renewals in 1-year increments. The post-doc must be a US citizen, resident alien, or nonresident alien who obtains a valid employment visa.

Applicants should submit a cover letter highlighting key qualifications and research interests, and curriculum vitae with complete bibliography to:

Andrew D. Johnson, Ph.D. at

The advertisement will remain open until the positions are filled.  PDF versions of documents sent by email are strongly preferred.

HHS and NIH are Equal Opportunity Employers.

Applications from women, minorities and persons with disabilities are strongly encouraged to apply. The NHLBI/NIH is a smoke freeworkplace. The NIH is dedicated to building a diverse community in its training and employment programs.


Sebastian Kurscheid, The Australian National University (AU), will give a seminar Aud. A, July 2 at 12h15pm

TAD cliques shape the 4-dimensional genome during terminal differentiation” 

Tuesday July 2nd, 12:15, Genopode, auditorium A


Genomic information is selectively used to direct spatial and temporal gene expression during differentiation. Interactions between topologically associated domains (TADs) and between chromatin and the nuclear lamina organize and position chromosomes in the nucleus. However, how these genomic organizers together shape genome architecture is unclear. Using a dual-lineage differentiation system, we report here long-range TAD-TAD interactions forming dynamic constitutive and variable TAD cliques. A differentiation-coupled relationship between TAD cliques and lamina-associated domains suggests that TAD cliques stabilize heterochromatin at the nuclear periphery. We also provide evidence of dynamic TAD cliques during mouse embryonic stem cell differentiation and somatic cell reprogramming, and of inter-TAD associations in single-cell Hi-C data. TAD cliques represent a new level of 4-dimensional genome conformation reinforcing the silencing of repressed developmental genes.

Trey Ideker will give a seminar – 4:30p.m. in Aud. A Génopode on July 16, 2019

DBC seminar

Dr. Trey Ideker , Professor of Medicine at UC San Diego on July 16th, at 4:30p.m. 


More about Trey Ideker (UC San Diego)


 Title: “Interpreting the cancer genome through physical and functional models of the cancer cell” 

 Date : Tuesday July 16th – 16h30

Location: Auditoire A – Génopode


Abstract of the talk: 

Recently we and other laboratories have launched the Cancer Cell Map Initiative ( and have been building momentum. The goal of the CCMI is to produce a complete map of the gene and protein wiring diagram of a cancer cell. We and others believe this map, currently missing, will be a critical component of any future system to decode a patient’s cancer genome. I will describe efforts along several lines: 1. Coalition building. We have made notable progress in building a coalition of institutions to generate the data, as well as to develop the computational methodology required to build and use the maps. 2. Development of technology for mapping gene-gene interactions rapidly using the CRISPR system. 3. Causal network maps connecting DNA mutations (somatic and germline, coding and noncoding) to the cancer events they induce downstream. 4. Development of software and database technology to visualize and store cancer cell maps. 5. A machine learning system for integrating the above data to create multi-scale models of cancer cells. In a recent paper by Ma et al., we have shown how a hierarchical map of cell structure can be embedded with a deep neural network, so that the model is able to accurately simulate the effect of mutations in genotype on the cellular phenotype.