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SENIOR BIOINFORMATICIAN (m/f/d)
60.000 € - 70.000 €
Join a growing Biostatistics team in Frankfurt! This is an opportunity to work on advanced analytics projects that improve current solutions and establish new ones. If you want to bring your own ideas and build up a new infrastructure this role as Bioinformatician will allow you to make an impact.
You will join a new team that is going to grow in the next few months. Parallel teams in other areas will give you the opportunity to share best practices and insights. The company actively encourages national and international knowledge sharing. You are going to collaborate with a wide range of stakeholders and are expected to embrace the culture of continuous learning in the company.
As Senior member of the team, you will take ownership to develop new pipelines and workflows to improve access to and quality of data. You will work with large and diverse datasets primarily supporting the genetics team. It is expected that you lead company wide projects to align data quality and validity. Therefore, excellent communication skills and motivation to manage stakeholders is needed. You will set strategic direction and help develop new algorithms for biological datasets. Additionally, you will support the digital transformation of the company and represent biotechnology in meetings and cross-functional projects.
YOUR SKILLS AND EXPERIENCE
HOW TO APPLY
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We were recently LIVE with Jonathan Ward, CEO and Co-Founder of Genome Biologics to discuss how AI, computational platforms and Data and Analytics have changed and accelerated the research and development of drugs in Biotech and Pharmaceuticals. Jonathan is a specialist in cardiovascular disease, one of the biggest killers globally. Annually, Cardiovascular Disease accounts for 17 million deaths, one-third of all deaths worldwide. His main line of work is in exploring and implementing how an integrated computational and biological approach to research and development can accelerate the creation of successful cardiovascular drugs, in a more financially and time efficient way. Genome Biologics was founded to spur the innovation that is often missing in the field of cardiovascular drugs. This unmet demand stems from the combination of expensive trials and high failure rates. However, Genome Biologics came up with a smart system, using both computational and biological systems, which allow the team to better predict failure before it happens. This amazing technology not only help increase success rates but makes the research more financially viable and a lot more attractive to potential investors. How does it all work? The team starts with the computational side. Here they screen large amounts of data which comes from a diverse range of sources, including public repositories, and the main aim of this process is to identify matches between gene expressions in heart disease or heart failure and a drug, or a mixture of drugs, that can change those gene expressions. The result of the gene therapy derives mostly from the integrated biological platform, where the team can validate the drugs used. Using real hearts, the team test the drugs screened by the computational research and see which ones improve the heart function. These drugs then go through the lengthy process of clinical trial which can take anywhere between seven to 15 years to complete. Using the technology for COVID-19 Jonathan and his team were approached early in the pandemic to see if their technology could help find a vaccine for COVID-19. Initially, the team said no due to the understanding that COVID-19 was a respiratory virus only. But as research continued and the virus was found to also affect the heart and other vital organs, Jonathan and his team looked at how they could apply their technology to identify any therapeutics. The team applied the computational system to filter out all the compounds within the coronavirus, looking at how these affected or changed the heart. The team were able to filter 5000+ compounds down to around 500 that were potentials for a repurposing approach to COVID-19. The idea was that they would be then be able to identify a drug, or a combination of drugs, that could boost the immune system and heart function to fight off the disease. In our event, Jonathan noted that, for all the vaccines being trialled and released to market over the past nine months, the computational approach has been favourable across the board from small labs to Pharma and Biotech giants, such as Pfizer. And, as we’ve seen in only the last few days, this approach has been incredibly successful as 90-year-old Margaret Keenan was one of the first people in the UK to vaccinated against COVID-19. Challenges for the industry post-pandemic COVID-19 has forced the Data and Life Science industry to evolve and adapt quickly and efficiently in order to work under pressure and find viable treatments in a much shorter timeframe than usual. The past nine months has most certainly provided learnings that the industry can take with them into any future work but, of course, the field constantly evolves, and this ever-changing nature will undoubtedly create hurdles to overcome. Genome Biologics explained that handling and managing data will be the biggest challenge for Biotech companies moving forward, simply because of the sheer scale and amount being produced. The volume of data, while important, is overshadowed by the need for high-quality data. As Jonathan points out, “If you put in junk, you get junk out” and so, the focus will very much be on getting hold of and using good data from reputable sources to ensure research and drug creation can be done efficiently and effectively. The future of data As we move forward, especially post COVID-19, there will be a lot more computational data analysis being used in the interpretation of medical information and data, which is both very advanced and exciting for the industry. However, this does mean that certain roles within the industry may become redundant, most likely pathologists. Pathologists are a large cost for many companies, as well as the hardest employees to source, making this element of research a very arduous and expensive problem. With the large uptake of computational systems, companies will be looking at creating a much cheaper and highly automated system. Not only will this reduce costs and time, but it will also greatly reduce the risks of human error in misinterpreting data. The further implementation of computational data in drug testing, means that there is a good chance human error could be eradicated from the industry in the next decade which would make a huge impact on the healthcare industry. Of course, there will always be limitations to consider. Here, no matter how good your computational platform is, you will always need the biological platform as the biological element is just as, important, if not more so, as the computational side. And so, humans will need to work together with advancements in technology to create an efficient and integrated system. Pharma, Biotech and drug discovery will never be a robot-only industry. Where should I start if I want to work in drug discovery? With decades of experience in the industry, Jonathan explains how to break into drug research, explaining that you need to have a clear understanding of the vision, mission and types of projects that are undertaken. Jonathan outlined, “Ultimately, it all depends on the kind of companies you want work for. What I can say however is that smaller Biotech companies are perfect for those who want hands-on work. These firms are more dynamic, you are likely to be involved in more projects and thrown into the deep end and ultimately learn a lot more. In big pharma, your experiences may be a little more limited across daily tasks, projects and progression.” There are a few key questions to look at as a professional already in the discipline: What can you contribute to the role that someone else can’t? What do you want to get out of the role? Working in drug discovery, research and a role that challenges a range of core issues in Life Science can be incredibly rewarding, but as Jonathan notes, “Make sure this job change is really what you want before you jump in. Like any role, do you research and get to know the role and company inside out.” Over the past nine months, Harnham has seen an increase in the number of in-demand positions across the Data Analytics and Life Science industry. With our unique understanding of this arena and excellent relationships with some of the best organisations around, whether you are a client or a candidate, we can offer bespoke solutions to suit your needs. If you’re hoping to change career or are looking for the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. To watch this LIVE event in full, please visit: https://www.linkedin.com/video/live/urn:li:ugcPost:6727579805614673920/
10. December 2020
The Life Science Analytics industry has always beaten to its own drum. But in the days of Covid-19, there’s a different feel and it’s one in which teams are coming together and candidates are staying longer in jobs where they feel connected and impactful. As the drive for a vaccine and the virtually overnight demand for telemedicine and contactless care come to bear, this industry which once seemingly fell behind that of retail and banking has caught up. So, what can businesses like biotech, pharmaceutical, and other healthcare providers do to retain and keep top candidates? EXPAND AND GROW YOUR TEAM LOCALLY AND GLOBALLY Reskill and Upskill for Career Advancement - If you’re lucky enough to have retained top talent, re-consider tenure-based positions. Advance your great candidates based on performance, need, upskilling, or reskilling. You may already have someone on staff who can do the job you need done or have the potential. Let them. The world has been moving faster than it ever has in this year alone its jumped into warp speed.Consider Global Collaboration – While many professionals, in every industry are working from home these days, some simply can’t due to the nature of their business. In this case, the need to be in the lab. However, as the Life Sciences & Analytics industry leads the way in their approach to flexible hours and the available Data on COVID-19, for example, global collaborations allow teams to do their work without the need for lab access.In demand technical skills - Candidates skilled in Data gathering, algorithm development, and predictive modeling are in high demand as well as AutoML, NLP, and other Machine Learning solutions. In demand soft skills – As the impact of the above technical skills increase and offer proven solutions, it will be important to have Data professionals who cannot only manage the technical side of things, but who can also explain solutions to the nontechnical and business executives in plain language. Since the start of the year, we’ve seen a massive shift in the way we do business. While for some businesses, it was business as usual for the most part. For others, it completely reinvented others. Healthcare and Life Sciences are no exception. And in the healthcare industry, they’ve been stretched in ways unimaginable just last year. And have learned a new respect for numbers and accurate Data. Two things vital to moving forward. A NEW RESPECT FOR NUMBERS AND ACCURATE DATA This new respect for accurate numbers and Data will help teams align to predict new threats while tracking current ones. In other words, no one will be caught off guard next time as the Life Sciences and Healthcare industry prepare for a post pandemic transformation. And how will it impact the industry moving forward? Work from home policies, global teams, telemedicine, the demand for PPE and ventilators, even the demands of the financial side of healthcare have shifted. But with the right data, innovation, and improved efficiency, it’s a sure bet the industry won’t be caught unawares again. WELCOME TO THE NEW NORMAL Though every profession has been hard hit during the pandemic, it’s the healthcare industry which has seen an even greater shift in the need demands to be met, shifting priorities, and patient care delivery has gone online. By moving forward with telemedicine and other automated services, the revenue cycle of the industry, too, has seen a shift. Yet to maintain business continuity, they must close the revenue gap. And here’s where Life Science Analytics meets FinTech and InsurTech. All of these industries will need Data professionals who can speak code and translate it to the nontechnical. All will need professionals with skillsets in predictive modelling, automation, Machine Learning, AI, and more. Is it you they’re looking for? If you’re interested in Data & Technology, Risk or Digital Analytics, Life Science Analytics, Marketing & Insight, or Data Science jobs we invite you to check out our current vacancies or get in touch with one of our expert consultants to find out more.
30. July 2020