Full-Time

Applications Scientist

Confirmed live in the last 24 hours

Schrödinger

Schrödinger

501-1,000 employees

Computational platform for biopharmaceutical research

No salary listed

Senior, Expert

Guildford, UK + 1 more

More locations: Dulwich, London, UK

Remote work is available in the UK (Greater London or the South East).

Category
Bioinformatics
Computational Biology
Biology & Biotech
Requirements
  • PhD in computational chemistry, bioinformatics, structural biology, or a related field
  • Deep scientific expertise in the modeling of nucleic acids (RNA/DNA) as a therapeutic modality or target
  • Experience in one or more of the following: molecular dynamics simulations/enhanced sampling/free energy calculation methods, ligand-based drug design, quantum mechanics, structural modeling
  • A solid understanding of the commercial drug discovery process
  • Excellent English language skills (both verbal and written)
  • Willingness to travel
Responsibilities
  • Provide scientific support to current and prospective customers, which includes demonstration of optimal use of our life science software suites, facilitation of interactions between customers and product development teams, and general scientific guidance
  • Engage in cutting-edge methodological scientific research and advise our customers on best practices for computational modelling
  • Publish scientific papers and present at conferences
Desired Qualifications
  • Postdoctoral research and/or relevant experience in the commercial sector
  • Expertise in the application of machine learning methods to drug discovery
  • Programming experience (preferably Python)
  • Experience with experimental techniques relevant to RNA/DNA-targeted drug discovery such as SHAPE-MaP, DMS-MaPseq, SPR, ITC, EMSA, FRET, cryo-EM, SAXS, and in vitro transcription/translation assays

Schrödinger provides a computational platform that aids in the research efforts of biopharmaceutical companies, academic institutions, and government laboratories around the world. Their platform offers advanced computational tools that help in drug discovery and research across various therapeutic areas. Schrödinger's products work by utilizing sophisticated algorithms and simulations to predict molecular behavior, which assists researchers in identifying potential drug candidates more efficiently. What sets Schrödinger apart from its competitors is its extensive global reach, serving clients in over 70 countries, and its dual focus on both software licensing and collaborative drug discovery programs. The company's goal is to advance scientific research and innovation by enhancing its computational platform and fostering partnerships in drug discovery.

Company Size

501-1,000

Company Stage

IPO

Headquarters

New York City, New York

Founded

1990

Simplify Jobs

Simplify's Take

What believers are saying

  • Schrödinger received $10M from Gates Foundation to enhance predictive toxicology tools.
  • The company's platform aids in early toxicity risk prediction, improving drug safety.
  • Schrödinger's collaboration with Avicenna accelerates lead-to-drug optimization using AI.

What critics are saying

  • Recursion and Exscientia's merger creates a strong competitor in AI drug discovery.
  • Avicenna's independent expansion could increase competition in medicinal chemistry.
  • High drug discovery costs may pressure Schrödinger to innovate and reduce expenses.

What makes Schrödinger unique

  • Schrödinger's platform supports diverse clients, including biopharma, academia, and government labs.
  • The company engages in both wholly-owned and collaborative drug discovery programs.
  • Schrödinger's computational tools are used in over 70 countries, showcasing global reach.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Company Match

401(k) Retirement Plan

Flexible Work Hours

Remote Work Options

Paid Vacation

Parental Leave

Company News

Silicon Canals
May 14th, 2025
Schrödinger to Present Phase 1 Clinical Data on MALT1 Inhibitor SGR-1505 at EHA Annual Congress and International Conference on Malignant Lymphoma

NEW YORK - (BUSINESS WIRE) - Schrödinger, Inc. (Nasdaq: SDGR) today announced that initial Phase 1 clinical data for SGR-1505, its investigational MALT1 inhibitor, will be presented at the European Hematology Association Annual Congress, taking place June 12 - 15, 2025, in Milan, Italy.

Charities.org
Apr 30th, 2025
Sustainability News provided by 3BL

Schrödinger launched its first company-wide Volunteer Month, during which every office globally participated in local community service activities.

Impact Global Health
Dec 3rd, 2024
The big global health R&D funding stories of 2024

Schrödinger have been awarded $19.5m by the Bill & Melinda Gates Foundation to use their platform to accelerate drug discovery for neglected diseases.

Securities.io
Aug 28th, 2024
Recursion And Exscientia Merger Create A New Ai Drug Discovery Leader

New Methods For Drug DiscoveryDiscovering new drugs has become increasingly expensive and complex in the last few decades, with new therapies costing more than a billion dollars to be developed.This is partly because all the low-hanging fruits are already picked, like known medicinal plants and “easy” to find biochemicals.Another factor is that the diseases yet to find an efficient treatment for are the most complex ones, often caused by a body complex dysfunction (diabetes, Alzheimer's, cancer, obesity, etc.) or hard-to-reach causes (for example parasites and viruses like HIV or malaria, very good at evading the immune system).This means that for discovering new molecules now, hundreds of thousands or even millions of compounds must be considered before narrowing it down to a few.This is a daunting task, and an expensive process as well.Luckily, progress in AI and computation has made it possible to comb through astronomical volume of data, at a much lower cost in both dollars and time.And two companies are now merging to speed up the adoption of AI-driven drug discovery.Exscientia Recursion MergerOn August 8th, 2024  the merger of Exscientia with its larger peer Recursion Pharmaceuticals was announced.Both companies had developed their own process to leverage AI and automation to speed up drug discovery, as well as reduce costs.A strong argument for the merger is that both companies' technologies are quite complementary. We will look in detail below at both companies, but the overall picture is such:Recursion is focused on “first-in-disease” opportunities, through a deeper understanding of biological mechanisms.Exscientia is focused on “best-in-class” drugs, with expertise in precision chemistry and molecular synthesis.So together, the combined company not only gets some additional scale to save money on overhead costs and regulatory compliance (usually the goal of mergers in biotech) but also the combination of excellence in chemistry synthesis AND biological insights.Exscientia The company is using AI to develop precision therapies.It runs a “full stack” AI drug discovery technology with dedicated software at every stage of the drug discovery process.So instead of looking at existing molecules, Exscientia’s Precision Design AI designs custom molecules to match the target found by its Precision Target AI.Exscientia's technology reduces 70% of the time required for going from a biological target to finding a corresponding drug and an 80% more capital-efficient process.Part of the time and cost saving comes from a highly automatized process, with “comprehensive robotic automation across the entire experimentation cycle”.This resulted in 4 compounds in early clinical stages, 30 programs in total, and $6.5B in revenues from milestones with partners. The main focus has been oncology (cancer) and inflammatory diseases.Recursion Pharma Recursion Pharmaceuticals leverages AI in drug discovery. The more AIs get involved in drug discovery and development, the more data will become precious for training the AIs.Biology is an extremely complex field, with integrated and verified data sometimes in short supply. This is a serious problem when any error will create bias, limitations, and errors in the AI, which might then need to be retrained from scratch.So creating solid datasets has been the focus of the company since its inception looking to solve several problems with biodata:Analog data, from faxes to pdf or scanned printouts.Siloed data, with little to no annotations.Hard to replicate research.To solve these problems, Recursion created one of the world's largest automated wet labs, and digitized millions of their own experiments (2.2 million experiments per week).It combines dry lab (in-silico) and wet lab (biological samples) with:A library of 1.7 million small molecules.Cell cultures, CRISPR gene editing, soluble factors, live viruses, etc.An automated laboratory robotics workflow that allows for up to 2.2 million experiments each week.High-throughput microscopes and sequencing systems.Continuous video feeds from cameras, recording holistic measurements of animal behaviors.Advanced computational resources, which have generated 21 petabytes of proprietary high-dimensional data.ADMET (absorption, distribution, metabolism, excretion, and toxicology) data.This creates unique (and massive) datasets at all levels of the “multiomics” biosciences, including proteomics (protein levels), transcriptomics (mRNA levels), phenomics (cellular morphology), ADMET and “in-vivonomics” (animal behaviors). The company is also looking to add metabolomics and genomics to its datasets in the future.(you can read more about why multiomics matters in “Multiomics Are The Next Step In Biotechnology”).So while Exscientia started by studying biological mechanisms and designing a drug for it, Recursion instead built from scratch a massive database of standardized and replicated biological research.Recursion also acquired in May 2023 the drug chemistry-focused preclinical startups, Cyclica and Valance, for a total of $87.5M.They also own one of the world's fastest supercomputers to train their LLMs and AIs for drug discovery

Genetic Engineering & Biotechnology News
Aug 7th, 2024
With $10M from Gates Foundation, Schrödinger Takes Aim at Toxicity Risk

Those discussions led to Schrödinger recently receiving a $10 million grant from the Gates Foundation toward expanding its computational platform to predict toxicity risk early in drug discovery.