This innovative biotechnology company powered by AI, wishes to grow by hiring a senior data scientist. They are the proprietors of a company that uses specialised machine learning algorithms to forecast immunogenic antigens for personalised cancer immunotherapy and infectious diseases like COVID-19. Knowing Norwegian is not required. Following your application Rebecca Jones, a specialist recruiter, will discuss the opportunity in detail. She will be more than happy to answer any questions relating to the industry and the potential for your career growth.

A disease capable of decimating and killing those affected, cancer involves cells in a specific part of the body growing and reproducing uncontrollably in a process known as proliferation. In a recent breakthrough, the tumor microenvironment (TME) has been established as a key driver for cancer progression, promoting resistance to therapeutics all the while enabling the disease to evade the immune system. Specifically, myeloid-derived suppressor cells (MDSCs) have been shown to play a central role in maintaining the TME through the suppression of host immunity, the establishment of new vasculature, and the remodeling of connective tissue to support tumor growth. Therefore, it is imperative to develop cancer immunotherapies able to promote the anti-oncological activity of the immune system with the dual ability to combat the highly detrimental effects of the TME. However, while it is straightforward to assess the effect of new therapies on cancer cells, estimating the effectiveness of these novel therapies on the TME is challenging.

Ludwig Cancer Research scientists have developed a new and more accurate method to identify the molecular signs of cancer likely to be presented to helper T cells, which stimulate and orchestrate the immune response to tumors and infectious agents. The study, led by David Gfeller and Michal Bassani-Sternberg of the Lausanne Branch of the Ludwig Institute for Cancer Research, is reported in the current issue of Nature Biotechnology. The new method combines two powerful new technologies. One is a mass spectrometry technology developed by Bassani-Sternberg's lab to rapidly and inexpensively obtain the amino acid sequences of thousands of peptide antigens--or protein fragments--bound to a molecular complex known as HLA that is expressed on the surface of cells. The other is a novel computational tool developed in Gfeller's lab that is based on machine learning, the computational approach that powers face-recognition software, among other things.

OncoImmunity AS will now become a subsidiary of NEC and operate under the name of NEC OncoImmunity AS. OncoImmunity AS, founded in 2014, is a bioinformatics company dedicated to the development of software solutions that facilitate the effective selection of patients for cancer immunotherapy, and identify optimal neoantigen targets for truly personalized cancer vaccines and cell therapies in a clinically actionable time frame. NEC announced its business strategy surrounding its AI-driven drug discovery business in May 2019. This acquisition is integral for enhancing the resources and capabilities that support the development of its individualized immunotherapy pipelines. NEC will maintain its focus on drug discovery, while NEC OncoImmunity AS continues its neoantigen prediction services.

"Spherical nucleic acids represent an exciting new class of medicines that are already in five human clinical trials for treating diseases, including glioblastoma (the most common and deadly form of brain cancer) and psoriasis," said Mirkin, the inventor of SNAs and the George B. Rathmann Professor of Chemistry in Northwestern's Weinberg College of Arts and Sciences. A new study published this week in Nature Biomedical Engineering details the optimization method, which uses a library approach and machine learning to rapidly synthesize, measure and analyze the activities and properties of SNA structures. The process, which screened more than 1,000 structures at a time, was aided by SAMDI-MS technology, developed by study co-author Milan Mrksich, Henry Wade Rogers Professor of Biomedical Engineering in Northwestern's McCormick School of Engineering and director of the Center for Synthetic Biology. Invented and developed at Northwestern, SNAs are nanostructures consisting of ball-like forms of DNA and RNA arranged on the surface of a nanoparticle. Researchers can digitally design SNAs to be precise, personalized treatments that shut off genes and cellular activity, and more recently, as vaccines that stimulate the body's own immune system to treat diseases, including certain forms of cancer.