Postdoctoral Fellow: Molecular Modelling & Machine Learning
AstraZeneca AB / Kemistjobb / Göteborg
2024-08-26
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hela Sverige Postdoctoral Fellow: Molecular Modelling & Machine Learning
Location: Gothenburg, Sweden
Competitive Salary, Bonus & Benefits Package
Do you have expertise in, and passion for Machine Learning, Computational Chemistry, Chemo-informatics or Immuno-informatics? Would you like to apply your expertise to impact computational immunology assessment in a company that follows the science and turns ideas into life-changing medicines? Then AstraZeneca might be the one for you!
About the Opportunity
In this exciting Postdoctoral Fellow position, you will research and develop computational tools for the prediction of immunogenicity risk for peptides and proteins incorporating non-natural amino acids.
This project is supported by the Computational Chemistry team within the Early Respiratory & Immunology function, which is centered on delivering life-changing products that improve health and fight and cure diseases. This team sits within the Medicinal Chemistry Department and supports all the pipeline development projects within the therapeutic area for small molecules and new modalities (peptides and oligonucleotides). The team also collocates in the Gothenburg in-silico Center of Excellence with dozens of other experts in the use of computational methods for drug-development.
This project is also supported by the Clinical Pharmacology & Safety Sciences (CPSS) group that works across all of AstraZeneca's therapy areas from early-stage drug discovery to late-stage clinical development.
The project will be in collaboration with an academic institution specializing in computational immunogenicity tools.
This is a 3-year program.
What you will do
Our Postdoctoral Fellow will conduct ground-breaking research using structure-based modelling and machine learning methods for prediction of immunogenicity. You will develop computational tools for immunogenicity assessment suitable for peptides and proteins incorporating non-natural amino acids. This will involve structural modelling of peptide-protein interactions, advanced computational methods to calculate binding affinities (e.g. Free Energy Perturbation) and utilizing state-of-the art machine learning techniques (e.g. transfer learning neutral networks).
Key Duties & Responsibilities:
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Research, design and implement innovative computational tools for immunogenicity assessment of peptides and proteins incorporating non-natural amino acids.
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Lead and drive the project under the supervision of cross-functional AstraZeneca team and in collaboration with the academic expert.
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Plan, write, publish, and present high-quality scientific papers.
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Participate in function and department activities in AstraZeneca, learn about drug discovery and development processes and get exposure to new scientific advances.
Essential Requirements
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PhD degree, or equivalent in computational biology / chemistry, or cheminformatics (with a significant data science component), or mathematics / machine learning.
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Experience with structure-based molecular modelling.
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Good knowledge of machine learning methods and data science concepts.
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Proficiency in programming (preferably Python).
Our Postdoc programme is aimed at individuals with a strong publication record who are either:
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Within 5-years of obtaining their doctoral degree (PhD, DVM, or MD) - PhD already awarded, or
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Students, soon to obtain doctoral degrees (the PhD must be awarded within 6 months of joining AstraZeneca).
Desirable Requirements
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Proven knowledge of one or more of the following areas: Immuno-informatics, Computational biology, Cheminformatics or Computational chemistry
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Excellent written and oral communication skills
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Strong planning, organizational and time management skills
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Ability to work effectively in a multidisciplinary research environment.
Reasons to Apply
You will work with the innovative technology in a highly collaborative environment to apply novel ideas to answer important questions addressing the safety of biological medicines. Immunogenicity represents a potential undesired safety risk for new biological therapeutic modalities. New modalities such as peptide-based therapeutics and antibody-drug conjugates frequently include non-natural amino acids. It is currently not possible to assess the immunogenicity risks resulting from such modifications computationally. By developing in silico tools to assess this risk you will help to deliver efficacious and safe medicines for our patients.
You will have several opportunities to work in collaboration with supportive cross-functional internal and external academic partners and engage with the external community, through publications in high-quality journals and presentations at conferences.
As a respected specialist, we will empower you to take appropriate risks, lead the project and "run with it", along with providing you will all the support you need.
On-Site Working
The position is located at our research site in Gothenburg, Sweden.
As a key member of a research group and taking a leading role on a Postdoctoral project, we expect regular attendance - a minimum of 3 days per week on the AstraZeneca campus. For laboratory-based scientists, this may be higher.
Next Steps
This advert will be running from August 26, 2024 and we welcome your application as soon as possible, but ahead of the scheduled closing date of September 15, 2024. In the event, that we identify suitable candidates ahead of the scheduled closing date, we reserve the right to withdraw the vacancy earlier than published.
Ersättning Not Specified
Så ansöker du Sista dag att ansöka är 2024-09-16
Klicka på denna länk för att göra din ansökan Arbetsgivarens referens Arbetsgivarens referens för detta jobb är "R-207702".
Omfattning Detta är ett heltidsjobb.
Arbetsgivare Astrazeneca AB (org.nr 556011-7482)
Arbetsplats AstraZeneca
Kontakt AstraZeneca
karolina.zingmark@astrazeneca.com Jobbnummer 8860729