PhD in cutting-edge leukemia research

MIRACLE-Leukemia, a new Marie Skłodowska-Curie doctoral network coordinated by Amsterdam UMC, is an international, multidisciplinary and multisectoral training program consisting of 23 academic and non-academic partners from 8 EU countries (The Netherlands, Belgium, Germany, France, Spain, Italy, Czech Republic, United Kingdom). 

We are looking for two PhD candidates for Amsterdam UMC that did not reside or carry out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the past 3 years.

The largest challenge associated with leukemia treatment is persistence of residual therapy-resistant cancer cells, called minimal residual disease (MRD), which underlies disease relapse and is responsible for the low survival rates of patients. Currently, knowledge on mechanisms of persistence of MRD and initiation of leukemia relapse is lacking, making development of therapeutics eradicating MRD difficult and hampering improvement of patient cure rates.

The new MIRACLE-Leukemia project will take an integrated, multidisciplinary and intersectoral approach to address the key unresolved questions on the molecular and cellular basis of acute leukemia MRD. MIRACLE is a Marie Skłodowska-Curie doctoral network, coordinated by Amsterdam UMC.

Read more on the website.

You will be trained to obtain a unique combination of skills in innovative high-tech technologies, advanced data analysis tools and artificial intelligence, organ-on-chip MRD models, and drug and immunotherapy testing, and will come up with innovative ideas to advance future leukemia treatment by integration of several disciplines and data sources.

Topics of the 2 MIRACLE research projects which will be hosted by Amsterdam UMC Hematology Department are:

1. Optimizing treatment decisions by using MRD data combined with artificial intelligence
   The aim of this research project is to better predict development and kinetics of minimal residual disease (MRD) and relapse in Acute Leukemic & Myeloid Leukemia (ALL & AML) over time by using multiparameter flow cytometry data measured at diagnosis and different time points after treatments in combination with artificial intelligence and bioinformatics. Moreover, the researcher will build mathematical prediction models discerning the best anti-leukemia efficacy of novel drugs and will find efficient combination strategies (for synergistic actions) potentially reducing MRD to increase disease-specific survival. For this, the researcher will use available data of drug testing experiments that have been performed in ALL and AML. Additionally, bioinformatic- and data science tools to integrate the data from different clinical trials, and different MRD biomarkers, including novel ones that will be identified within the network (both leukemia specific and environmental (immune) factors) will be created. Moreover, new advanced analytical data portals to integrate data from different platforms of the same material and derived from different materials, generated within and outside of this network will be developed. The ultimate goal of this project is to generate products to support shared medical decision making based on better estimates of treatment outcomes using more and better data, which will finally result in the improvement of treatment outcome and patient.
   As part of the project, you will also work at MIRACLE Partner ORTEC B.V. to develop artificial intelligence to dynamically follow MRD and obtain knowledge on business development, and at MIRACLE Partner Charles University (2 months, Czech Republic) to analyze single cell RNA (scRNA) sequencing data using novel bioinformatic tools.
2. Characterization of AML MRD using single cell transcriptomic and epigenetic analysis
   This project aims to capture the heterogeneity of AML MRD, and identify characteristics of MRD during treatment. The researcher will work in close collaboration with a wet-lab technician to deconstruct MRD-specific features using integrative analysis of scRNA- and single cell assay for transposase-accessible chromatin (scATAC)-sequencing, in combination with single cell protein profiling. The leukemic (stem cell-like) phenotype of the cells, microenvironment components, and immune cells will be identified by highly multiplexed protein quantification using TotalSeq antibodies. The researcher will make use of AML (poor risk) patient samples at diagnosis, MRD and relapse and AML patient cells purified from an AML patient derived xenograft (PDX) mouse model treated with chemotherapy or venetoclax-based therapy. Selected genes (e.g. related to senescence and cytokine signaling) from the single cell data and previously identified, will be tested for their expression in AML and ALL patient samples and for their functionality as MRD biomarkers and therapy targets. Next, the researcher will in close collaboration with DC5 test the identified genes for their efficiency to function as targets for anti-MRD therapeutics, using small in vivo CRISPR knock-out screens. Based on results of the CRISPR-Cas9 screening, therapy strategies will be designed and tested, using ex vivo primary AML (stem/progenitor) assays, AML PDX mouse models and “organ on chip” MRD models.
   You will also work at VIB-KU Leuven Center for Cancer Biology (4 months, Belgium) to analyze scRNA sequencing data and to set up in vivo CRISPR-Cas9 screening, and at Ospedale San Raffaele SRL (3 months, Italy) to study therapy-induced senescence-associated factors as anti-MRD therapy targets.

We are looking for two PhD candidates.

1. Profile for Optimizing treatment decisions by using MRD data combined with artificial intelligence: Master’s degree in life sciences, other (bio)medical sciences, or related and proficiency in bioinformatics and R and/or artificial intelligence.
2. Profile for Characterization of AML MRD using single cell transcriptomic and epigenetic analysis: Master’s degree in Bioinformatics, Computational Biology, Biomedical sciences or a related field. Experience with cancer biology, transcriptomics or epigenetics and/or experience with data analysis (e.g., single cell ATAC-Seq or RNA-Seq).

Important additional requirements are:

• You comply with the transnational mobility rule of the Marie Skłodowska-Curie doctoral network. You did not reside or carry out your main activity (work, studies, etc.) in the country of the host organisation for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status are not considered.
• You hold a MSc or equivalent degree in a subject specified in the description of the individual PhD projects.
• You have the necessary academic skills and background to make the success of a doctoral degree. The skills needed will depend on the project chosen.
• You demonstrate high level of proficiency in written and spoken English, which will be assessed with the motivation letter and the interview, respectively.
• You have a strong interest in conducting international collaborative research.
• You do not hold a PhD degree or have successfully defended your PhD. 
• You fulfil the local requirements and must be eligible to enrol the PhD programme at the host institution.
• You are an ambitious, dedicated professional with solid social skills.